Individual Model Components Research Articles

Innovative Positioning during the Placement of a Peripherally Inserted Central Catheter (PICC)

Modern construction projects are complex engineering structures that vary in purpose, materials, height, the regulatory period of service, purpose and features of operation. Often there is a need for reconstruction of old buildings and structures. All this requires the development of technologies, methods, and special equipment for the inspection of buildings and constructions, quality control not only in the course production but also at the construction site. The use of control devices allows solving problems of contractors non-compliance with the requirements of the project and the consequences of incorrect assembly, which in turn may lead not only to economic losses but also to the damage caused to the health and lives of people. In this article, we have designed a device for measuring the diameter of reinforcement concrete structures. For modeling of individual components of the electronic part of device the system NI Multisim is used. For modeling of electromagnetic sensors for developed the device for measuring the diameter of the reinforcement concrete structures the program Maxwell SV is used.

Good modelling practice in applying computational fluid dynamics for WWTP modelling.

Computational fluid dynamics (CFD) modelling in the wastewater treatment (WWT) field is continuing to grow and be used to solve increasingly complex problems. However, the future of CFD models and their value to the wastewater field are a function of their proper application and knowledge of their limits. As has been established for other types of wastewater modelling (i.e. biokinetic models), it is timely to define a good modelling practice (GMP) for wastewater CFD applications. An International Water Association (IWA) working group has been formed to investigate a variety of issues and challenges related to CFD modelling in water and WWT. This paper summarizes the recommendations for GMP of the IWA working group on CFD. The paper provides an overview of GMP and, though it is written for the wastewater application, is based on general CFD procedures. A forthcoming companion paper to provide specific details on modelling of individual wastewater components forms the next step of the working group.

A dynamic landslide hazard assessment system for Central America and Hispaniola

Abstract. Landslides pose a serious threat to life and property in Central America and the Caribbean Islands. In order to allow regionally coordinated situational awareness and disaster response, an online decision support system was created. At its core is a new flexible framework for evaluating potential landslide activity in near real time: Landslide Hazard Assessment for Situational Awareness. This framework was implemented in Central America and the Caribbean by integrating a regional susceptibility map and satellite-based rainfall estimates into a binary decision tree, considering both daily and antecedent rainfall. Using a regionally distributed, percentile-based threshold approach, the model outputs a pixel-by-pixel nowcast in near real time at a resolution of 30 arcsec to identify areas of moderate and high landslide hazard. The daily and antecedent rainfall thresholds in the model are calibrated using a subset of the Global Landslide Catalog in Central America available for 2007–2013. The model was then evaluated with data for 2014. Results suggest reasonable model skill over Central America and poorer performance over Hispaniola due primarily to the limited availability of calibration and validation data. The landslide model framework presented here demonstrates the capability to utilize globally available satellite products for regional landslide hazard assessment. It also provides a flexible framework to interchange the individual model components and adjust or calibrate thresholds based on access to new data and calibration sources. The availability of free satellite-based near real-time rainfall data allows the creation of similar models for any study area with a spatiotemporal record of landslide events. This method may also incorporate other hydrological or atmospheric variables such as numerical weather forecasts or satellite-based soil moisture estimates within this decision tree approach for improved hazard analysis.

Roles of Phosphodiesterases in Cyclic Nucleotide Cross-Talk in Cardiac Myocytes

The cyclic nucleotides (cNs) cAMP and cGMP regulate the response of cardiac myocytes to both external and internal stimuli. Distinctly-regulated phosphodiesterases (PDEs) control the degradation of these cNs. As a result of their regulation by cNs, PDEs also facilitate communication between the β-adrenergic and Nitric Oxide (NO)/cGMP/Protein Kinase G (PKG) signaling pathways, which regulate the synthesis of cAMP and cGMP, respectively. Activation of the β-adrenergic pathway potentiates cardiac contractility, whereas activation of the NO/cGMP/PKG pathway reduces it. As a result, the balance between cNs plays a critical role in regulating contraction. The phenomena where cAMP influences the dynamics of the cGMP pathway, and vice versa, are commonly referred to as cN cross-talk. However, the cross-talk response and the individual role of each PDE isoenzyme in shaping this response remain to be fully characterized. We have developed a computational model of the cN cross-talk network that mechanistically integrates the β-adrenergic and NO/cGMP/PKG pathways via regulation of PDEs by both cNs. The individual model components and the entire network model replicate experimentally observed activation-response relationships and temporal dynamics. The model predicts that under sub-maximal β-adrenergic stimulation, an increase of PDE2 and a decrease of PDE3 cAMP hydrolysis rates under concomitant NO stimulation results in a net cAMP accumulation, leading to the observed NO-mediated potentiation of Protein Kinase A (PKA) activation. In addition, under concomitant β-adrenergic stimulation, due to cGMP accumulation from increased PDE5 and decreased PDE3 cGMP hydrolysis rates, PKG can be further activated beyond the level achieved under NO alone. By defining cN cross-talk reactions based on the binding affinity of cNs to specific PDE domains and the associated hydrolysis rates, we pin-pointed the principal mechanisms driving the cross-talk response within this non-linear, tightly-coupled reaction system.

High Precision Device for Diameter Rebar Control in Reinforced Concrete Products

Modern construction projects are complex engineering structures that vary in purpose, materials, height, the regulatory period of service, purpose and features of operation. Often there is a need for reconstruction of old buildings and structures. All this requires the development of technologies, methods, and special equipment for the inspection of buildings and constructions, quality control not only in the course production but also at the construction site. The use of control devices allows solving problems of contractors non-compliance with the requirements of the project and the consequences of incorrect assembly, which in turn may lead not only to economic losses but also to the damage caused to the health and lives of people. In this article, we have designed a device for measuring the diameter of reinforcement concrete structures. For modeling of individual components of the electronic part of device the system NI Multisim is used. For modeling of electromagnetic sensors for developed the device for measuring the diameter of the reinforcement concrete structures the program Maxwell SV is used.

A multi-model ensemble approach to seabed mapping

Seabed habitat mapping based on swath acoustic data and ground-truth samples is an emergent and active marine science discipline. Significant progress could be achieved by transferring techniques and approaches that have been successfully developed and employed in such fields as terrestrial land cover mapping. One such promising approach is the multiple classifier system, which aims at improving classification performance by combining the outputs of several classifiers. Here we present results of a multi-model ensemble applied to multibeam acoustic data covering more than 5000km2 of seabed in the North Sea with the aim to derive accurate spatial predictions of seabed substrate. A suite of six machine learning classifiers (k-Nearest Neighbour, Support Vector Machine, Classification Tree, Random Forest, Neural Network and Naïve Bayes) was trained with ground-truth sample data classified into seabed substrate classes and their prediction accuracy was assessed with an independent set of samples. The three and five best performing models were combined to classifier ensembles. Both ensembles led to increased prediction accuracy as compared to the best performing single classifier. The improvements were however not statistically significant at the 5% level. Although the three-model ensemble did not perform significantly better than its individual component models, we noticed that the five-model ensemble did perform significantly better than three of the five component models. A classifier ensemble might therefore be an effective strategy to improve classification performance. Another advantage is the fact that the agreement in predicted substrate class between the individual models of the ensemble could be used as a measure of confidence. We propose a simple and spatially explicit measure of confidence that is based on model agreement and prediction accuracy.

Enhancement and integration of desiccant evaporative cooling system model calibrated and validated under transient operating conditions

Desiccant cooling systems provide new possibilities in air conditioning technology through the use of either solid or liquid sorption air dehumidification. Such systems can be more reliable and environmental friendly than the conventional systems. The focus of current study is to enhance the existing ideal system component models of the desiccant evaporative cooling system (DEC) developed in an equation-based object-oriented modeling and simulation program, Dymola/Modelica to address the real component operation. Initially, the enhanced component models are calibrated and validated through the transient measurements obtained from the real DEC system installation. Afterward, using the validated physical models of individual components, complete system model has been experimentally calibrated and validated. The obtained results are in good agreement with the actual measurements at the both component and system levels. At the system level, in terms of specific enthalpy of supply air, the resulting maximum and minimum root mean square error (RMSE) and mean percentage error (MPE) between the simulated and measured transient performance is 0.96 kJ/kg and 1.53%. The results show that the enhanced system model is able to predict the performance of the real desiccant cooling system with good accuracy. As such, the current paper contributes to the efforts of bringing simulations closer to performance of real systems under building operating conditions.

Noise, sampling, and the number of projections in cone-beam CT with a flat-panel detector.

To investigate the effect of the number of projection views on image noise in cone-beam CT (CBCT) with a flat-panel detector. This fairly fundamental consideration in CBCT system design and operation was addressed experimentally (using a phantom presenting a uniform medium as well as statistically motivated "clutter") and theoretically (using a cascaded systems model describing CBCT noise) to elucidate the contributing factors of quantum noise (σ(Q)), electronic noise (σ(E)), and view aliasing (σ(view)). Analysis included investigation of the noise, noise-power spectrum, and modulation transfer function as a function of the number of projections (N(proj)), dose (D(tot)), and voxel size (b(vox)). The results reveal a nonmonotonic relationship between image noise and N(proj) at fixed total dose: for the CBCT system considered, noise decreased with increasing N(proj) due to reduction of view sampling effects in the regime N(proj) <~200, above which noise increased with N(proj) due to increased electronic noise. View sampling effects were shown to depend on the heterogeneity of the object in a direct analytical relationship to power-law anatomical clutter of the form κ/f(β)--and a general model of individual noise components (σ(Q), σ(E), and σ(view)) demonstrated agreement with measurements over a broad range in N(proj), D(tot), and b(vox). The work elucidates fairly basic elements of CBCT noise in a manner that demonstrates the role of distinct noise components (viz., quantum, electronic, and view sampling noise). For configurations fairly typical of CBCT with a flat-panel detector (FPD), the analysis reveals a "sweet spot" (i.e., minimum noise) in the range N(proj) ~ 250-350, nearly an order of magnitude lower in N(proj) than typical of multidetector CT, owing to the relatively high electronic noise in FPDs. The analysis explicitly relates view aliasing and quantum noise in a manner that includes aspects of the object ("clutter") and imaging chain (including nonidealities of detector blur and electronic noise) to provide a more rigorous basis for commonly held intuition and heurism in CBCT system design and operation.

Constructive epistemic modeling of groundwater flow with geological structure and boundary condition uncertainty under the Bayesian paradigm

• BMA trees of model weights, prediction and variance serve as a learning tool. • Candidate propositions are tested to learn about individual model components. • Posterior model probability is a degree of belief given our state of knowledge. • Geological structure uncertainty is larger than boundary condition uncertainty. • Model structure uncertainty is larger than parameter uncertainty. Constructive epistemic modeling is the idea that our understanding of a natural system through a scientific model is a mental construct that continually develops through learning about and from the model. Using hierarchical Bayesian model averaging (BMA), this study shows that segregating different uncertain model components through a BMA tree of posterior model probability, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool. First, the BMA tree of posterior model probabilities permits the comparative evaluation of the candidate propositions of each uncertain model component. Second, systemic model dissection is imperative for understanding the individual contribution of each uncertain model component to the model prediction and variance. Third, the hierarchical representation of the between-model variance facilitates the prioritization of the contribution of each uncertain model component to the overall model uncertainty. We illustrate these concepts using the groundwater flow model of a siliciclastic aquifer-fault system. We consider four uncertain model components. With respect to geological structure uncertainty, we consider three methods for reconstructing the hydrofacies architecture of the aquifer-fault system, and two formation dips. We consider two uncertain boundary conditions, each having two candidate propositions. Through combinatorial design, these four uncertain model components with their candidate propositions result in 24 base models. The study shows that hierarchical BMA analysis helps in advancing knowledge about the model rather than forcing the model to fit a particularly understanding or merely averaging several candidate models.

Modeling Techniques for a Computational Efficient Dynamic Turbofan Engine Model

A transient two-stream engine model has been developed. Individual component models developed exclusively in MATLAB/Simulink including the fan, high pressure compressor, combustor, high pressure turbine, low pressure turbine, plenum volumes, and exit nozzle have been combined to investigate the behavior of a turbofan two-stream engine. Special attention has been paid to the development of transient capabilities throughout the model, increasing physics model, eliminating algebraic constraints, and reducing simulation time through enabling the use of advanced numerical solvers. The lessening of computation time is paramount for conducting future aircraft system-level design trade studies and optimization. The new engine model is simulated for a fuel perturbation and a specified mission while tracking critical parameters. These results, as well as the simulation times, are presented. The new approach significantly reduces the simulation time.

Simulation of variable refrigerant flow air conditioning system in heating mode combined with outdoor air processing unit

Variable refrigerant flow (VRF) air conditioning system has become attractive due to better energy performances than traditional air conditioning systems. However, the shortcoming of no outdoor air (OA) intake has not been solved thoroughly. A new VRF and outdoor air processing unit combined air conditioning system is proposed and simulated. The first obstacle is that there is no well-known simulation tool for VRF unit in heating mode. A VRF model of condenser-number independence is developed and validated first. The combined system is modeled by integrating the individual sub-system or component models into a complete system. The average error of the developed model to predict heating capacity, input power and COP are 7.87%, 12.45% and 6.19% respectively. Finally the combined system is simulated under conditions of the same and different set-points of the air conditioning zones. The combined system could maintain all the zones at their specific set-points within small errors no matter the set-points are the same or different. Moreover, indoor air quality can be ensured. The demand of one air conditioning system possessing independent units serving separate zones in the same building could be met by the combined system.

Multi‐FPGA digital hardware design for detailed large‐scale real‐time electromagnetic transient simulation of power systems

Large-scale electromagnetic transient simulation of power systems in real-time using detailed modelling is computationally very demanding. This study introduces a multi-field programmable gate array (FPGA) hardware design for this purpose. A functional decomposition method is proposed to map FPGA hardware resources to system modelling. This systematic method lends itself to fully pipelined and parallel hardware emulation of individual component models and numerical solvers, while preserving original system characteristics without the need for extraneous components to partition the system. Proof-of-concept is provided in terms of a 3-FPGA and 10-FPGA real-time hardware emulation of a three-phase 42-bus and 420-bus power systems using detailed modelling of various system components and iterative non-linear solution on a 100 MHz FPGA clock. Real-time results are compared with offline simulation results, and conclusions are derived on the performance and scalability of this multi-FPGA hardware design.

Low voltage model for the study of slow disturbances in medium voltage grids

The proliferation of both, sensitive and pollutant loads at the users equipment has placed the power quality issue as an important challenge for facilities and utilities. Power system simulation programmes are powerful tools to study the generation and propagation of disturbances in order to establish a feed back with the measuring plans.The main difficulty with power system simulation programmes applied to power quality studies in medium voltage networks is the accuracy of the model of the network itself, in particular that of the loads. Numerous load models of individual LV components are reported in the literature. If the composition of these loads at different sites is adequately known, the aggregation method adapted with field measurements may be used to obtain a global load model for higher voltage network levels. These methods present a weakness since the measurements are carried out in the steady state or, in the best case, in the pre and post steady states for the long time disturbances leading, therefore, to non-accurate results.This paper presents a technique to obtain a LV load model adapted for the study of the long duration disturbances, also called slow disturbances, which goes beyond the classical methods and also exploits the measurements ‘during’ a long time disturbance. This model combines a static and a dynamic components which take into account the power consumption of the passive and active loads of an industrial plant. The process for obtaining the model will be explained and the results of the proposed models in ATP-EMTP environment are verified against the measured voltage and current waveforms.

Clay hypoplasticity with explicitly defined asymptotic states

A new rate-independent hypoplastic model for clays is developed. The model is based on the recently proposed approach enabling explicit incorporation of the predefined asymptotic state boundary surface and corresponding asymptotic strain rate direction into hypoplasticity. Several shortcomings of the existing hypoplastic model for clays are identified and corrected using the proposed approach. Thanks to the independent formulation of the individual model components, the new model is more suitable to form a basis for further developments and enhancements than the original one.

Integrated irradiance modelling in the urban environment based on remotely sensed data

The complexity of built form and land cover has often limited detailed model estimates of solar irradiance in the urban canopy. These limitations arise largely from difficulties in generating contiguous detailed spatial representations of solar obstructing features such as buildings and trees. This study presents a method that integrates remotely sensed datasets across spatial scales for estimating irradiance in urban areas. The method draws largely on airborne Light Detection and Ranging (LiDAR) technology with specific focus on estimating radiation transmission through urban vegetation. The incoming irradiance above the urban canopy is determined using atmospheric transmission derived from geostationary satellite imagery to provide a long-term record of seasonal fluctuations in cloud cover, and the associated direct and diffuse irradiance. Individual model components are analyzed for three urban study areas to assess the interactions between input model parameters and patterns of different urban form. Results indicate that representations of trees as opaque objects substantially underestimate solar irradiance across urban form types, demonstrating up to a 18% underestimate of direct irradiance in treed residential areas. Both atmospheric transmittance and urban form are also shown to be critical model parameters, and are discussed with reference to unique considerations for generating estimates of urban irradiance.

Parameter sensitivity of a watershed-scale flood forecasting model as a function of modelling time-step

Although ongoing technological advances have alleviated data restrictions and most of the computational barriers to distributed modelling, lumped, parsimonious, conceptual and rainfall-runoff models are still widely used for flood forecasting. However both optimum parameter values and the fluxes of water through individual model components change significantly with the time-step used. Thus, such models should be used with caution in applications such as hydrograph separation or water quality studies that require the fluxes through individual flow routes through the model or which try to relate parameters to physical features of the catchment. To demonstrate this time-scale limitation, a parameter sensitivity analysis was performed on the lumped conceptual Soil Moisture Accounting and Routing with Groundwater component (SMARG) model for a 182 km2 rural catchment in Ireland for a number of time-steps, flow regimes and evaluation metrics. A global sensitivity analysis method (Higher Dimensional Model Representation) showed that sensitivity indices vary greatly with time-step and evaluation metric. The sensitivity of parameters also varied for different flow regimes. Certain parameters' sensitivities remain fairly constant across both flow regimes and time-step, while others are very much regime or time-step dependent. Care should be taken in using internal information from conceptual models because of this strong dependence on time-step.

Use of contexts in language model interpolation and adaptation

Language models (LMs) are often constructed by building multiple individual component models that are combined using context independent interpolation weights. By tuning these weights, using either perplexity or discriminative approaches, it is possible to adapt LMs to a particular task. This paper investigates the use of context dependent weighting in both interpolation and test-time adaptation of language models. Depending on the previous word contexts, a discrete history weighting function is used to adjust the contribution from each component model. As this dramatically increases the number of parameters to estimate, robust weight estimation schemes are required. Several approaches are described in this paper. The first approach is based on MAP estimation where interpolation weights of lower order contexts are used as smoothing priors. The second approach uses training data to ensure robust estimation of LM interpolation weights. This can also serve as a smoothing prior for MAP adaptation. A normalized perplexity metric is proposed to handle the bias of the standard perplexity criterion to corpus size. A range of schemes to combine weight information obtained from training data and test data hypotheses are also proposed to improve robustness during context dependent LM adaptation. In addition, a minimum Bayes’ risk (MBR) based discriminative training scheme is also proposed. An efficient weighted finite state transducer (WFST) decoding algorithm for context dependent interpolation is also presented. The proposed technique was evaluated using a state-of-the-art Mandarin Chinese broadcast speech transcription task. Character error rate (CER) reductions up to 7.3% relative were obtained as well as consistent perplexity improvements.

Transients in Wind Power Plants—Part I: Modeling Methodology and Validation

This is the first part of a two-paper series and presents the modeling methodology for all of the main components of a typical wind power plant for power system transient studies. The models developed are intended for investigation of the temporary overvoltages, switching overvoltages, and lightning overvoltages. The component models developed include the high-frequency models of the vacuum and SF6 circuit breakers, three core cables for the collector grid, and quad core cables for the wind turbine tower, turbine transformer, doubly fed asynchronous generator, and surge arrester. The models developed are wideband in nature and can be used for all studies, except the transformer model which requires two variations for the low–mid frequency range and mid–high frequency range. Detailed user-defined models developed for both vacuum and SF6 circuit breakers take account of the restrikes, reignitions, prestrikes, low-frequency high-current interruption, and high-frequency low-current interruption. The generator and transformer transient models include a representation of the various high-frequency capacitive couplings. The success criteria for each individual component model are discussed, and the model performance is validated against these criteria.

Field Data for Evaluating 2010 Highway Capacity Manual Operational Analysis Methodology for Interchange Ramp Terminals

Interchange ramp terminals provide connections between various highway facilities (freeway–arterial, arterial–arterial, freeway–freeway, etc.), so their efficient operation is essential. NCHRP Project 3–60 developed analysis methods for evaluating the operational performance of signalized interchange ramp terminals. Those methods were based primarily on simulated data. Further research used collected field data to evaluate the interchange analysis methodology developed under NCHRP Project 3–60 to identify application limitations and to suggest improvements. Data were collected at eight sites representing various types of interchanges with different geometric and traffic characteristics. Video cameras, mounted on existing poles on the side of the road and on nearby buildings, were used to gather traffic operation data, including demand, lane utilization, and queue length at each site. The research evaluated both individual analytic model components (such as lane utilization factors and internal queue length) and the performance of the interchange (reflected in average queue lengths and control delay). Overall, the models performed well. However, large discrepancies were observed when operating conditions of the interchange were close to capacity. The queue length prediction at the beginning of the upstream arterial or ramp phase was calibrated to modify the effective green time estimation. A new lane utilization model was based on field data for a four- or five-lane external arterial approach where the two leftmost lanes were extensions of the downstream dual left turn lanes. The findings of the work were incorporated into the 2010 Highway Capacity Manual.

Stability Study for a Hybrid AC-DC More-Electric Aircraft Power System

The paper deals with the small-signal stability analysis of aircraft ac frequency-wild power systems representing a real ac-dc hybrid distribution architecture with a multiplicity of actuators, aircraft loads, and bus geometries. The <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$dq$</tex> modelling approach is applied to derive individual power system component models and to constitute the corresponding generalized power system model as a powerful and flexible stability analysis tool. The element models can be interconnected in an algorithmic way according to a variety of the architecture selected. Intensive time-domain simulation and experimental results are used to verify the theoretical results. It is also shown how the proposed approach can be used to predict instability due to possible variations in operating points and system parameters.