System-level Behavior Research Articles

Load quantification of the wheel–rail interface of rail vehicles for the infrastructure of light rail, heavy rail, and commuter rail transit

The type and magnitude of loads that pass through the track superstructure have a great impact on both the design and the performance of the concrete crossties and fastening systems. To date, the majority of North American research that focus on quantifying the rail infrastructure loading conditions has been conducted on heavy-haul freight railroads. However, the results and recommendations of these studies may not be applicable to the rail transit industry due to a variety of factors. Unlike the freight railroads, which have standardized maximum gross rail loads and superstructure design practices for vehicles, the rail transit industry is home to a significant variety of vehicle and infrastructure designs. Some of the current transit infrastructure design practices, which were established decades ago, need to be updated with respect to the current loading environment, infrastructure types, and understanding of the component and system-level behavior. This study focuses on quantifying the current load environment for light rail, heavy rail, and commuter rail transit infrastructure in the United States. As an initial phase of this study, researchers at the University of Illinois at Urbana-Champaign (UIUC) have conducted a literature review of different metrics, which is used to evaluate the static, dynamic, impact, and rail seat loads for the rail transit infrastructure. UIUC will compare these methods and their computed values to determine which provide the most accurate depictions of the expected loading condition given a set of operating and infrastructure characteristics. A proper load quantification of rail transit systems, gained through an improved understanding of the load path and rail seat load, will help to establish the basis for developing recommendations for a mechanistic design process for the rail transit infrastructure components. Ultimately, the results of this research will allow transit agencies to increase the effectiveness of their capital spending and transit agencies will have the potential to improve safety, ride quality, capacity, and the life cycle of the rail transit infrastructure.

Impact of delayed information in sub-second complex systems

What happens when you slow down the delivery of information in large-scale complex systems that operate faster than the blink of an eye? This question just adopted immediate commercial, legal and political importance following U.S. regulators’ decision to allow an intentional 350 microsecond delay to be added in the ultrafast network of financial exchanges. However there is still no scientific understanding available to policymakers of the potential system-wide impact of such delays. Here we take a first step in addressing this question using a minimal model of a population of competing, heterogeneous, adaptive agents which has previously been shown to produce similar statistical features to real markets. We find that while certain extreme system-level behaviors can be prevented by such delays, the duration of others is increased. This leads to a highly non-trivial relationship between delays and system-wide instabilities which warrants deeper empirical investigation. The generic nature of our model suggests there should be a fairly wide class of complex systems where such delay-driven extreme behaviors can arise, e.g. sub-second delays in brain function possibly impacting individuals’ behavior, and sub-second delays in navigational systems potentially impacting the safety of driverless vehicles.

A Bottom-up Simulation Method to Quantitatively Predict Integrated Care System Performance

Introduction : The demographic development resulting shows that the population distribution has already changed considerably and will further change over the next decades. That is, the number of older people with chronic conditions will increase intensively. This expected increase of older people in society poses an immense challenge to the public health care system. The integrated care could be a promising concept in redesigning care to tackle this. However, changing from conventional public healthcare policy to integrated care requires a lot of feasibility studies, and major health policy changes often has wide-ranging impacts on our community, the evidence of process redesign interventions regarding their ability to improve quality of care must be interpretable for populations. Furthermore, integrated care systems are made up of an interconnected set of relationships between individuals, organizations and groups, all of which have unique aims, motivations, beliefs and cultures. Given this complexity, it is very difficult to evaluate the impact of a major policy change through unilateral research, modelling or consultation processes, and efficient management of integrated care system also becomes a big challenge. Simulation can be used for dynamic as opposed to static analysis of integrated care system. Our research started from simulating Emergency Departments (EDs) in public healthcare system. Our ultimate aim is to model the entire integrated care pathway, from management of health in the home to acute care and provision of specialist services. Methods : Integrated care system is a large, dynamic, complex environment. In this circumstance, not only accuracy in prediction, interpretability is also extremely important to have transparency in predictive modeling. Domain experts as well as civilian populations do not tend to prefer black box predictive models. They would like to understand how predictions are made, and possibly, prefer models that emulate the way a human expert might make a decision with a few important variables, and a clear convincing reason to make a particular prediction. An agent-based model (ABM) (also called individual-based models) is a class of computational models for simulating the actions and interactions of entities (individual or collective entities such as organizations, departments) with a view to assessing their effects systematically as a whole. Therefore, we used ABM technique to simulate the complex integrated system from bottom up, that is, simulate the behavior of care staff and patient, and interactions among them. The system performance as a whole will emerge from these interactions. Our AMB for simulating EDs was carried out by analyzing historical data (to determine the nature of distributions and transition probabilities), and conducting interviews with experienced healthcare staff (to establish comprehensive understanding). Results : The developed simulation model has been calibrated and validated using actual data from Hospital de Sabadell. This model provides a flexible platform for studying ED operations as it predicts the system-level behavior from micro-level interaction. In this mode, the effect of policies on parameters such as waiting times and throughput could be quantified before actual implementing. Discussion : The integrated care system comprises of many stakeholders and the underlying processes involve a lot of interaction among patients and service providers. To some extend, any one of the entities in the system is significant, has big influence on overall system performance. The proposed method has two potential usages in integrated care: (1) before implementing, the simulator (built according to proposals) can work as a virtual prototype to verify policies, (2) in the management of integrated care system, the simulator (polished according to actual system) can be used to predict system performance under unexperienced scenarios (like flu pandemia), so as to avoid overcrowding, and evaluate proposed changes before implementing. Of course simulations can never be a perfect model for reality, and it is important to understand their limitations, but they can provide substantially more information than theoretical research. Conclusion : Start from simulating the emergency departments, our efforts proved the feasibility and ideality of using agent-based model & simulation techniques to study healthcare system. The framework developed in our work is a step towards building a full model of integrated care system. The final model will be able to represent a comprehensive tool to quantitatively evaluate prospective planned changes to the integrated care system for decision making, and open a wide field of possible simulation scenarios for a better understanding of the integrated care complex system. In conclusion, bottom-up simulations can help understand how the different elements of integrated care system work together under different conditions. It is a crucial pre-requisite for improving the coordination and integration of care, and increasing the efficiency of resource allocation. This research has been supported by the MINECO Spain, under contract TIN2014-53172-P and has been partially supported by China Scholarship Council (CSC) under reference number: 201306290023.

Real-Time Device-Level Transient Electrothermal Model for Modular Multilevel Converter on FPGA

Real-time simulation of modular multilevel converters (MMCs) is challenging due to their complex structure consisting of a large number of submodules (SMs). In the literature, the computational speed is emphasized for MMC modeling in real-time simulation, while accurate and detailed information of insulated-gate bipolar transistor (IGBT) modules in SMs is sacrificed. A novel datasheet-based device-level electrothermal model for an MMC on the field programmable gate array (FPGA) is presented in this paper for real-time hardware emulation. Conduction and switching power losses, junction temperatures, temperature-dependent electrical parameters, and linearized switching transient waveforms of IGBT modules are adequately captured in the proposed model. Simultaneously the system-level behavior of the MMC is accurately modeled. Five-level and nine-level MMC systems are emulated in the hardware with the time step of 10 $\bm {\mu }\text{s}$ and 10 $\text{ns}$ for system-level and device-level computations, respectively. The paralleled and pipelined hardware design using IEEE 32-bit floating point number precision runs on Xilinx Virtex-7 XC7VX485T device. The emulated real-time results by an oscilloscope have been validated by offline simulation on SaberRD software.

CFD Systems Level Modeling of a Protonic Ceramic Fuel Cell

There is a critical need for intermediate-temperature fuel cells that offer low-cost, distributed generation both at the system and device levels. Current development work at the Colorado School of Mines is being carried out for a mixed proton and oxygen-ion-conducting electrolyte that enables fuel-cell operation at temperatures less than 500°C. By using a proton- and oxygen-ion-conducting electrolyte, the fuel cell stack is able to reduce coking which clogs anodes with carbon deposits and enhance the process of turning hydrocarbon fuels into hydrogen. Today's solid-oxide fuel cells (SOFCs) are based on oxygen-ion conducting electrolytes and operate at high temperatures. Advanced mixed proton- and oxygen-ion-conducting fuel cells operate at lower temperatures, and have the capacity to utilize hydrogen, ethanol, methanol, or methane fuels. Additionally, an advanced single-step sintering process has been developed to reduce manufacturing costs of these protonic-ceramic fuel cells (PCFC). “Solid-state reactive sintering” reduces the number of manufacturing steps from 15 to 3, drastically decreasing costs. Understanding the systems-level behavior of the PCFC is critical to enable its emergence as a roll-out technology. The team at Calif. State Polytechnic Univ. at Pomona is performing numerical modeling of the PCFC system. The goal of this poster is to present results of Computational Fluid Dynamic (CFD) systems level modeling of a typical PCFC stack having a cylindrical shape factor. The configuration is modeled using commercial CFD software which can easily be benchmarked using experimental data. The flow is H2 on anode side and air on the cathode side. Flow rates are on the order of 100 sccm for each side. The interconnect between each cell is made of ferritic stainless steel (70% Fe, 27% Cr, 1% Y2O3). The operation of a PCFC is fundamentally different than SOFCs due to their ability to conduct protons as well as oxygen ions across a dense ceramic electrolyte. Two global electrochemical reactions are needed since the material is capable of conducting two charged defects. One global reaction is the result of proton conduction across the electrolyte, and the other is the result of oxygen-ion transport across the electrolyte. Similar to SOFCs, heterogeneous internal reforming of hydrocarbons such as methane and water-gas-shift reactions still occur on the nickel phase of the anode. However, since minimal water is generated in the anode from the electrochemical reactions, the reforming reactions must be supplied with an external water source, such as an external waste heat recovery boiler or via anode gas recycle. Additionally, the low temperature operation tends to shift the equilibrium composition of the fuel species toward higher methane content (i.e., lower conversion of internal reforming reaction) where hydrogen partial pressures in the anode will be limited by thermodynamics. The difference in operating temperatures and the removal of hydrogen from the anode via electrochemical oxidation can also influence the optimal steam-to-carbon ratio (S/C) required to avoid solid carbon deposition when compared to SOFCs. The above-described electromechanical kinetics are incorporated into the systems-level CFD model of the PCFC presented in this poster. Results for CFD based Multi-physics of the electro-mechanical PCFC behavior for mole fraction vs. temperature, fuel utilization vs. temperature, voltage potential vs. current density, and power density vs. current density are presented in the poster. Figure 1

Electrochemical Reduction from a Single Particle to the Systems Level

Understanding electrochemical behavior requires inquiry of the material fundamental properties as well as the behavior of the material when configured into a fully functioning device. Thus, the ability to use local electrochemical probes and integrate the results with system level behavior is needed. In this work, quantitative electrochemistry was conducted on individual particles of vanadium phosphorous oxides, (specifically SVPO, AgwVxPyOz) cathode materials. Silver ions incorporated into the layered vanadium phosphorous oxide structure facilitated monitoring of the reaction progress through the formation of silver metal. The results obtained from the single particle were related to the systems level through in-situ examination of the reduction progress in fully assembled cells probed through energy dispersive x-ray diffraction, EDXRD. At the particle level, individual particles of active material, Ag2VO2PO4, were electrochemically reduced to various depths of discharge. After the material was reduced, the conductivity of the individual particles was determined using a nanoprobe integrated with a scanning electron microscope, Fig. 1. The individual particles showed a drastic reduction in local resistance when discharged. At the system level, in situ energy dispersive X-ray spectroscopy (EDXRD) was used to probe Li/ Ag2VP2O8 cells at several stages of reduction, allowing depth profile analysis of the discharge process. This technique enables micron scale spatial resolution of reduced Ag2VP2O8 and Ag0 discharge products in the bulk electrode. Results suggest the formation of a 3-dimensional Ag0 percolation network that increases conductivity throughout the entire electrode, occurs concurrently with a substantial decrease in the charge transfer resistance. The resistance of the reduced cathode is dependent upon discharge rate even in the presence of conductive additives. Development of the next generation of battery systems with improved energy utilization requires accessing all of the active material in an electrode. The multiscale inquiry methodology described provides a template for future investigations of both particle level and system level properties of electrochemically discharged materials highlighting the importance of advanced instrumental techniques to gain insight into complex discharge processes. Figure 1

Abstract P2-05-18: Mesofluidic platform for high throughput screening of inhibitors of metastasis

Abstract A fundamental limitation in the development of new therapies to prevent metastatic cancer is a lack of in vitro systems that can accurately recapitulate the steps of cancer cell metastasis. Currently, most assays for examining the steps of metastasis fail to incorporate the biophysical forces experienced by tumor cells due to blood flow, or are low throughput and thereby not amenable to drug screens or high throughput experimentation. We have developed a novel high throughput mesofluidic platform for assaying cell adhesion under flow in a 96-well format. This device functions like a cone and plate viscometer in each well by inducing shear stress on cells cultured in a standard 96-well plate. We validated the fluid flow and alignment of the device and studied the adhesion of cultured leukocytic monocytes (THP-1 cells) and multiple cancer cell lines (MDA-MB-231 and MCF-7 breast cancer cell lines) to purified extracellular matrix molecules (ECM), endothelial cells and immobilized platelets. Assays were carried out under flow (0.5 dynes/cm2 shear stress) and static conditions. Our studies show that adhesion assays performed under flow yield markedly different results from static adhesion assays. Treatment of breast cancer cells with a small library of integrin inhibitors demonstrated that these compounds had minimal effect on cancer cell adhesion to endothelial cells or immobilized platelets under static conditions, whereas under shear conditions many of these compounds significantly reduced adhesion of cancer cells. As well, this experiment elucidated integrins important for breast cancer adhesion to endothelial cells and platelets. A static adhesion assay of breast cancer cells to various types of ECM showed greater adhesion of the less aggressive MCF-7 cell line in comparison to the more aggressive MDA-MB-231 cell line. In contrast, flow incorporating assays showed increased adhesion of the more aggressive MDA-MB-231 breast cancer cell line. Specifically, the shear assay saw a significant increase in adhesion for multiple ECM as well as an increase in the strength of adhesion to laminin. Finally, we performed a high throughput screening experiment using a kinase inhibitor library of 80 compounds and found that the shear based assay yielded notably different results from a similar screen under static conditions for breast cancer cell adhesion to endothelial cells, immune cell adhesion to endothelial cells and breast cancer cell adhesion to platelets. This shear experiment yielded seven "hits", many of which match targets of drugs in clinical trials. In conclusion, our studies show that adhesion assays performed under flow yield markedly different results from static adhesion assays, and are better at identifying both aggressive cancer cells lines and known pathways for circulating cancer and immune cell adhesion. Thus, this high-throughput screening platform may enable the development of novel compounds to inhibit cancer metastasis and facilitate the study of the systems level behavior of cancer-endothelium adhesion. Citation Format: Spencer A, Spruell C, Nandi S, Le V, Crexiell M, Dunn AK, Baker AB. Mesofluidic platform for high throughput screening of inhibitors of metastasis. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-05-18.

Evolutionary Connectionism: Algorithmic Principles Underlying the Evolution of Biological Organisation in Evo-Devo, Evo-Eco and Evolutionary Transitions.

The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term “evolutionary connectionism” to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions.

A Design Pattern for Decentralised Decision Making.

The engineering of large-scale decentralised systems requires sound methodologies to guarantee the attainment of the desired macroscopic system-level behaviour given the microscopic individual-level implementation. While a general-purpose methodology is currently out of reach, specific solutions can be given to broad classes of problems by means of well-conceived design patterns. We propose a design pattern for collective decision making grounded on experimental/theoretical studies of the nest-site selection behaviour observed in honeybee swarms (Apis mellifera). The way in which honeybee swarms arrive at consensus is fairly well-understood at the macroscopic level. We provide formal guidelines for the microscopic implementation of collective decisions to quantitatively match the macroscopic predictions. We discuss implementation strategies based on both homogeneous and heterogeneous multiagent systems, and we provide means to deal with spatial and topological factors that have a bearing on the micro-macro link. Finally, we exploit the design pattern in two case studies that showcase the viability of the approach. Besides engineering, such a design pattern can prove useful for a deeper understanding of decision making in natural systems thanks to the inclusion of individual heterogeneities and spatial factors, which are often disregarded in theoretical modelling.

Hybrid simulation for system-level structural response

Hybrid simulations combine physical and analytical components into a single simulation to evaluate the response of a structure, often under seismic ground motion. This allows an experiment to be conducted in which structural components with complex response can be modeled experimentally and more well-known components can be represented within an analytical model. The coordination software UI-SimCor, developed by the MUST-SIM NEES facility at the University of Illinois at Urbana–Champaign, is a hybrid simulation tool which performs the dynamic analysis and other software and hardware coordination tasks for hybrid simulations. In many hybrid simulations, including those that have used UI-SimCor, analytical models with few effective degrees of freedom are typically used. In simulations where system-level behaviors and the response of the analytical components are of importance, a more detailed analytical system is needed. This changeover to a more complex analytical system and increase in general complexity of the hybrid simulation can cause various issues within the UI-SimCor framework. This study discusses the difficulties and issues that arise from having large and complex analytical substructures in hybrid simulation, and the effective mitigation or solutions to those problems.

Abstract LB-008: Mesofluidic platform for high throughput screening for inhibitors of metastasis

Abstract Background: A fundamental limitation in the development of new therapies to prevent metastatic cancer is a lack of in vitro systems that can accurately recapitulate the steps of cancer cell metastasis. Currently, most assays for examining the steps of metastasis fail to incorporate the biophysical forces experienced by tumor cells due to blood flow, or are low throughput and therefore not amenable to drug screening and high throughput experimentation. Methods: We have developed a novel high throughput mesofluidic platform for assaying cell adhesion under flow in a 96-well format. This device functions like a cone and plate viscometer in each well by inducing shear stress on cells cultured in a standard 96-well plate. We validated the fluid flow and alignment of the device and studied the adhesion of cultured leukocytic monocytes (THP-1 cells) and multiple cancer cell lines (HCT116, MDA-MB-231 and MCF-7 cells) to purified extracellular matrix molecules (ECM), endothelial cells and immobilized platelets. All assays were carried out under flow (0.5 dynes/cm2 of shear stress) and static conditions. Results: Our studies show that adhesion assays performed under flow yield markedly different results from static adhesion assays, and are better at identifying both aggressive cancer cells lines and known pathways for circulating cancer and immune cell adhesion. Treatment of breast cancer cells with a small library of integrin inhibitors demonstrated that these compounds had minimal effect on cancer cell adhesion to endothelial cells under static conditions, whereas under shear conditions many of these compounds reduced adhesion of cancer cells. In addition, a static adhesion assay of breast cancer cells to various types of ECM showed higher adhesion of the less aggressive MCF-7 cell line in comparison to the more aggressive MDA-MB-231 cell line. In contrast, flow incorporating assays showed increased adhesion of the MDA-MB-231 in comparison to the MCF-7 cell line. Finally, we performed a high throughput screening experiment using a kinase inhibitor library with 80 compounds and found that the shear based assay yielded notably different results from a similar screen under static conditions for cancer cell adhesion to endothelial cells, immune cell adhesion to endothelial cells and cancer cell adhesion to platelets. Conclusions: Our studies show that adhesion assays performed under flow yield markedly different results from static adhesion assays, and are better at identifying both aggressive cancer cells lines and known pathways for circulating cancer and immune cell adhesion. Thus, this high-throughput screening platform may enable the development of novel compounds to inhibit cancer metastasis and facilitate the study of the systems level behavior of cancer-endothelium adhesion. Citation Format: Adrianne Shearer, Chris Spruell, Victoria Le, Mar Creixell, Seema Nandi, Aaron B. Baker. Mesofluidic platform for high throughput screening for inhibitors of metastasis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-008. doi:10.1158/1538-7445.AM2015-LB-008

Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach.

Drought is one of the major environmental stress conditions affecting the yield of rice across the globe. Unraveling the functional roles of the drought-responsive genes and their underlying molecular mechanisms will provide important leads to improve the yield of rice. Co-expression relationships derived from condition-dependent gene expression data is an effective way to identify the functional associations between genes that are part of the same biological process and may be under similar transcriptional control. For this purpose, vast amount of freely available transcriptomic data may be used. In this study, we consider gene expression data for different tissues and developmental stages in response to drought stress. We analyze the network of co-expressed genes to identify drought-responsive genes modules in a tissue and stage-specific manner based on differential expression and gene enrichment analysis. Taking cues from the systems-level behavior of these modules, we propose two approaches to identify clusters of tightly co-expressed/co-regulated genes. Using graph-centrality measures and differential gene expression, we identify biologically informative genes that lack any functional annotation. We show that using orthologous information from other plant species, the conserved co-expression patterns of the uncharacterized genes can be identified. Presence of a conserved neighborhood enables us to extrapolate functional annotation. Alternatively, we show that single ‘guide-gene’ approach can help in understanding tissue-specific transcriptional regulation of uncharacterized genes. Finally, we confirm the predicted roles of uncharacterized genes by the analysis of conserved cis-elements and explain the possible roles of these genes toward drought tolerance.

Towards heterotic computing with droplets in a fully automated droplet-maker platform.

The control and prediction of complex chemical systems is a difficult problem due to the nature of the interactions, transformations and processes occurring. From self-assembly to catalysis and self-organization, complex chemical systems are often heterogeneous mixtures that at the most extreme exhibit system-level functions, such as those that could be observed in a living cell. In this paper, we outline an approach to understand and explore complex chemical systems using an automated droplet maker to control the composition, size and position of the droplets in a predefined chemical environment. By investigating the spatio-temporal dynamics of the droplets, the aim is to understand how to control system-level emergence of complex chemical behaviour and even view the system-level behaviour as a programmable entity capable of information processing. Herein, we explore how our automated droplet-maker platform could be viewed as a prototype chemical heterotic computer with some initial data and example problems that may be viewed as potential chemically embodied computations.

Modeling for (physical) biologists: an introduction to the rule-based approach

Models that capture the chemical kinetics of cellular regulatory networks can be specified in terms of rules for biomolecular interactions. A rule defines a generalized reaction, meaning a reaction that permits multiple reactants, each capable of participating in a characteristic transformation and each possessing certain, specified properties, which may be local, such as the state of a particular site or domain of a protein. In other words, a rule defines a transformation and the properties that reactants must possess to participate in the transformation. A rule also provides a rate law. A rule-based approach to modeling enables consideration of mechanistic details at the level of functional sites of biomolecules and provides a facile and visual means for constructing computational models, which can be analyzed to study how system-level behaviors emerge from component interactions.

Analysis of Electrochemical Reactions on Irregular Pores Structures Relevant to Batteries and Fuel Cells Electrodes

Porous electrodes are important in the applications of fuel cells and batteries by increasing reaction surface area. Systematic understanding of the effect of different pore structures of electro-catalyzed reactions will improve electrode efficiency and, in general, optimize the design of electrochemical processes occurring in fuel cell and batteries. Electrode systems are analyzed by using models to obtain useful system’s information. This information helps in predicting system level behaviors and assessing experimental results relevant to the design and operation of these pore-based systems. The present work uses analytical models to analyze zero order and first order electrochemical reactions occurring in irregular pore structures applicable for fuel cells and batteries. The electrochemical processes at the electrode pores are modeled by employing the microscopic species mass conservation equation with diffusion in the pore domain and electrochemical reactions present at the boundaries. The microscopic equation is scaled up to the macroscopic pore level by employing an area averaging-based approach to obtain a system level information applicable to practical systems. The area averaged solutions are verified by comparing them with exact solutions based on separation of variables for the ideal cases. Results obtained from the macroscopic equation identified potential deviations in the predicted concentration profiles as the deviation from ideal domains increases. The results predict an important role of the pore geometry on effecting the overall system efficiency as well as the convergence of the averaged solution to the exact solution. This study suggests useful guidelines for modelling and experimentation of complex systems.

System-Theoretic Analysis of a Class of Battery Equalization Systems: Mathematical Modeling and Performance Evaluation

Battery equalizers are widely used in multibattery systems to maintain balanced charge among individual battery cells. While the research on the hardware realization of battery equalizers has received significant attention, rigorous analysis of the battery equalization process at the system level remains largely unexplored. In this paper, we study three types of battery equalization system structures: series-based, layer-based, and module-based. Specifically, we derive mathematical models that describe the system-level behavior of the battery equalization processes under these equalization structures. Then, based on the mathematical models, analytical methods are developed to evaluate the performance of the equalization processes. In addition, we carry out statistical analysis to compare the performance of the three equalization structures considered.

A systematic review of agent-based modelling and simulation applications in the higher education domain

This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a ‘bottom-up’ modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro). This approach of considering the behaviour of systems of interacting ‘agents’ has been applied to a wide variety of domains. Of particular interest, are the ways that ABMS applications have been used to further understand the dynamics of the HE domain. We conduct a systematic review of literature to analyse publications by year, role of the simulator, development stage of the models, and any associated validation. We also identify areas for future work, which includes an emphasis on validating existing and future models, detailed description of simulations to allow replication and further development, and the use of agent-based models in other contexts within the increasingly complex HE domain.

Tailoring Healthy Workplace Interventions to Local Healthcare Settings: A Complexity Theory-Informed Workplace of Well-Being Framework.

Many healthy workplace interventions have been developed for healthcare settings to address the consistently low scores of healthcare professionals on assessments of mental and physical well-being. Complex healthcare settings present challenges for the scale-up and spread of successful interventions from one setting to another. Despite general agreement regarding the importance of the local setting in affecting intervention success across different settings, there is no consensus on what it is about a local setting that needs to be taken into account to design healthy workplace interventions appropriate for different local settings. Complexity theory principles were used to understand a workplace as a complex adaptive system and to create a framework of eight domains (system characteristics) that affect the emergence of system-level behaviour. This Workplace of Well-being (WoW) framework is responsive and adaptive to local settings and allows a shared understanding of the enablers and barriers to behaviour change by capturing local information for each of the eight domains. We use the results of applying the WoW framework to one workplace, a UK National Health Service ward, to describe the utility of this approach in informing design of setting-appropriate healthy workplace interventions that create workplaces conducive to healthy behaviour change.

A Modeling Framework for Studying Quantum Key Distribution System Implementation Nonidealities

Quantum key distribution (QKD) is an innovative technology that exploits the laws of quantum mechanics to generate and distribute unconditionally secure shared key for use in cryptographic applications. However, QKD is a relatively nascent technology where real-world system implementations differ significantly from their ideal theoretical representations. In this paper, we introduce a modeling framework built upon the OMNeT++ discrete event simulation framework to study the impact of implementation nonidealities on QKD system performance and security. Specifically, we demonstrate the capability to study the device imperfections and practical engineering limitations through the modeling and simulation of a polarization-based, prepare and measure BB84 QKD reference architecture. The reference architecture allows users to model and study complex interactions between physical phenomenon and system-level behaviors representative of real-world design and implementation tradeoffs. Our results demonstrate the flexibility of the framework to simulate and evaluate current, future, and notional QKD protocols and components.

Performance assessment of steel–concrete composite bridges with subsurface deck deterioration

In-service composite steel girder bridges typically experience a variety of deterioration mechanisms during their service lives, ranging from cracking, spalls, and delaminations in the reinforced concrete deck to corrosion in the steel girders. To date, several inspection techniques and novel technologies have been widely implemented to identify and measure different sources of defects associated with bridge systems, especially within the concrete deck. Despite successful implementation of these evaluation methodologies, what transportation agencies still lack is a fundamental understanding of the system-level behavior and the potential impact of the identified deterioration conditions on the overall performance of these bridges.In this paper, the impact of corrosion-induced subsurface deck delamination on the overall behavior and performance of steel–concrete composite bridges is investigated using finite element simulation and analysis. The accuracy and validity of the modeling approaches were assessed through a comparison to experimental data available in literature. A sensitivity study was performed to investigate the influence of deck deterioration on the system-level performance, load distribution behavior, and failure characteristics of two representative composite steel girder bridges. One of the selected structures is a full-scale laboratory bridge model, while the other one is an actual in-service structure with geometrical characteristics that represents typical features of steel girder bridges in Virginia.The selected damage scenarios included variations in different geometrical characteristics such as location and depth of damage, as well as degradation in material properties at the corresponding damaged areas. In addition to the bridge system behavior, the impact of rebar corrosion and subsurface delamination on the behavior of individual deck systems was investigated; while its implication on the current design methodologies for reinforced concrete decks was evaluated. Results from this investigation demonstrate that the deck deterioration has minimal impact on the overall system behavior and the path to failure of the selected structures, but may impact the failure characteristics in the form of reductions in the ultimate load-carrying capacity and system ductility.