System-level Performance Research Articles

Objective-Oriented Health Systems Reform

ABSTRACT This paper emphasizes the importance of orienting health system reforms to address underlying system-level performance problems. Too often in practice, the objective-orientation that is stressed in health system frameworks gets lost in relation to policies or schemes that are promoted without plausible linkages to the actual objectives of the reforms. The objective-orientation can also get subsumed by political agendas that are disconnected, or can even detract from, people’s health needs. There are three core attributes to objective-oriented health system reform: (i) problem-oriented; (ii) consistent (extent to which reforms are connected to the problems they are meant to address and reflect lessons from global and national experience); and (iii) continuously evaluated. Country experiences reviewed in the paper, and presented in this special issue, illustrate how taking an objective-orientation led reformers to alter the details of implementation. Continuous learning also informed adaptations needed to strategically sequence and link reforms with objectives. An objective-oriented approach enables reformers to: (i) seize windows of opportunity; (ii) find room to maneuver under the label of the reform; (iii) integrate applied research into reform implementation; and (iv) skillfully interpret political statements to align with technical best practices. The approach and attributes laid out in this paper put forward considerations for policy makers as they design, implement, evaluate, and adapt policies to feasibly improve health system performance. They also, importantly, help guard against a rush toward policies or schemes that may sound good in speeches or declarations but do not have a plausible link to objectives.

Health care utilization and costs among coordinated care patients in Southeastern Ontario: A difference-in-differences study of a double propensity score-matched cohort.

Coordinated care plans (CCPs) for high-cost health care system users aim to improve system-level performance. We evaluated health care resource use and costs among CCP patients (enrollees) versus a control group that did not receive coordinated care (comparators) in Southeastern Ontario. A difference-in-differences analysis of a quasi-experimental, double propensity score-matched and adjusted cohort was conducted. Linked population-based administrative data were used to measure health care utilization and costs and to identify comparators for two enrollee groups who began CCPs between April 1, 2013, and March 31, 2019. Enrollees were recruited from hospitals in Quinte or community care centres in Rural Hastings/Thousand Islands, and were 1:1 propensity score matched to comparators. Difference-in-differences estimates were calculated using generalized estimating equations for hospitalization rates, homecare visits, primary care visits, other health care resources and total costs. A total of 558 enrollees in Quinte and 538 in Rural Hastings/Thousand Islands were identified and matched to comparators. Difference-in-differences estimates were significant in both enrollee groups for number of homecare visits ([IRR 1.72; 95% CI (1.44, 2.06)] and [IRR 1.73; 95% CI (1.45, 2.06)], respectively). Number of primary care visits were 1.76 times greater for Rural Hastings/Thousand Islands enrollees versus comparators [IRR 1.76; 95% CI (1.32, 2.35)]; total costs increased by 23% ([IRR 1.23; 95% CI (1.09,1.39)]. Homecare use significantly increased for enrollees versus comparators, indicating specific priority areas of Ontario CCPs were met. However, no reductions were shown for other health system performance indicators. We also showed increased 7-day primary care follow-up visits for community care centre-recruited patients, but not for hospital-recruited patients. Decision-makers may wish to target patients who are less advanced in their chronic disease trajectory.

Aero-optical effects, part II. Sources of aberrations: tutorial

This paper serves as part II of a two-part tutorial on “aero-optical effects.” In part I, we provide introductory material with an emphasis on system-level considerations, particularly for those who are new to the field of aero-optics. In part II, we move on to survey several sources of aberrations. For example, we cover foundational sources like boundary layers and shear layers, as well as miscellaneous sources like mechanical contamination, shock waves, and aero acoustics. Throughout part II, we emphasize drivers for system-level performance, which appropriately builds on the system-level considerations covered in part I. This emphasis will inform future efforts looking to develop airborne-laser systems flying at subsonic, supersonic, and hypersonic speeds.

Effect of superheat degree on the performance of an organic Rankine cycle system that utilizes a wet working fluid

AbstractLimited experimental research has been conducted on organic Rankine cycle (ORC) systems that use wet working fluids. Therefore, the present study examined how the performance of an ORC system that uses a wet working fluid (R134a) was affected by the superheat degree ratio (SDR) under various scroll rotation speeds. The SDR is the dimensionless ratio between superheat degree and evaporation temperature at a given heat source temperature. Experimental results indicated that at scroll rotation speeds of 900, 1350, and 1800 rpm, the maximum output power of the aforementioned system was 1103, 1464, and 1537 W, respectively, with SDRs of 0.49, 0.49, and 0.54, respectively. The maximum net efficiencies at these speeds were 5.87%, 5.91%, and 5.32%, respectively, which occurred at SDRs of 0.61, 0.49, and 0.48, respectively. This level of system performance was attributable to the high enthalpy at the expander inlet and the high mass flow rate at the high evaporation pressure under an SDR of approximately 0.5. Although increasing the SDR did not enhance the scroll expander's isentropic efficiency, this efficiency decreased considerably when the SDR fell below 0.2. These findings emphasize the importance of optimizing the SDR of ORC systems to improve their performance.

Performance evaluation and analysis for hydraulic active suspension using the collaborative control method

Hydraulic active suspension has the coupling characteristics of integrated mechanical-hydraulic-control system, and its performance is also affected by external interference, noise interference, and other factors. Therefore, a novel controller is presented to achieve system-level optimal performances by using the collaborative control method. The proposed collaborative method is provided an implementation framework, and includes outer loop control of Linear Quadratic Regulator (LQR), inside loop control of modified linearized active disturbance rejection control (M-LADRC) and Kalman filter, and so on. In addition, the semi-physical simulation method is used to the simulation and test, and the force tracking control test for hydraulic servo system and Kalman filter test are carried out. Finally, the performance of semi-physical active suspension is compared with that of the ideal active suspension and passive suspension under the different road profile excitation. The superiority and effectiveness are verified for the collaborative control method. The collaborative controller has improved the suspension system performance and is more practical, which is beneficial for the application of the achievements.

Reliability of Girder Bridge System under Lateral Uneven Vehicular Overloads

Truck presence on bridges is random. Trucks may centrically or eccentrically appear on a bridge span in one or more lanes, which will cause extra load effects on girder components and eventually influence structural performance. Especially when trucks are heavily loaded, their eccentric passage is possible to induce damage in components, and, thus, the prescribed load- delivery path will be changed among components within the system. Therefore, component- and system-level structural performance of bridges subjected to aggressive vehicular overloads need to be thoroughly addressed. In this study, a WIM-based 5-axle overloaded truck model is chosen, and it is gradually applied to the finite element models of two girder bridges with different eccentric distance, considering two loading scenarios of single truck and multiple trucks. In detail, trucks are transversely loaded with an incremental eccentric distance, to investigate the impacts of eccentric loadings on structural performance, including failure sequences of components, load distribution factors among components, as well as system redundancy, as structures entering nonlinear stage. Finally, the reliability indices of the two bridges under uneven overloads are assessed at the component level and system level, respectively. The results of this study were beneficial to structural evaluation bridges subjected to overloads to ensure their serviceability and integrity.

Product Design Incorporating Competition Relations: A Network-Based Design Framework Considering Local Dependencies

Abstract System design has been facing the challenges of incorporating complex dependencies between individual entities into design formulations. For example, while the decision-based design framework successfully integrated customer preference modeling into optimal design, the problem was formulated from a single entity’s perspective, and the competition between multiple enterprises was not considered in the formulation. Network science has offered several solutions for studying interdependencies in various system contexts. However, efforts have primarily focused on analysis (i.e., the forward problem). The inverse problem still remains: How can we achieve the desired system-level performance by promoting the formation of targeted relations among local entities? In this study, we answer this question by developing a network-based design framework. This framework uses network representations to characterize and capture dependencies and relations between individual entities in complex systems and integrate these representations into design formulations to find optimal decisions for the desired performance of a system. To demonstrate its utility, we applied this framework to the design for market systems with a case study on vacuum cleaners. The objective is to increase the sales of a vacuum cleaner or its market share by optimizing its design attributes, such as suction power and weight, with the consideration of market competition relations, such as inter-brand triadic competition involving three products from different brands. We solve this problem by integrating an exponential random graph model (ERGM) with a genetic algorithm. The results indicate that the new designs, which consider market competition, can effectively increase the purchase frequency of specific vacuum cleaner models and the proposed network-based design method outperforms traditional design optimization.

Developing and reporting a healthcare-associated infection composite score for health system board review

Background One strategy for supporting a hospital or health system's board of directors (Board), with their quality oversight responsibility is to review the organization's performance on quality measures. But for large systems, the number of measures needing review is quite burdensome and makes priority setting difficult. Our goal was to develop a scoring method that summarizes multiple quality measures together, while still maintaining the Board's opportunity to examine individual measures where there are specific concerns. Methods We calculated an overall health system-level composite performance score using six publicly reported healthcare-associated infections reported by the Centers for Medicare and Medicaid Services on their Care Compare website [central-line associated bloodstream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), surgical site infections (SSIs) for colon surgery and abdominal hysterectomy, hospital-onset Methicillin-resistant Staphylococcus aureus bacteremia (MRSA), and hospital-onset Clostridioides difficile ( C. diff)], where relative weights assigned to each infection type reflect the severity of patient harm. We also calculated a health-system composite performance target. For individual infection types, we calculated system-wide scores and targets and categorized individual hospital performance into three performance categories. Results The health system's composite score between 2015 and 2019 ranged from a high of 1.10 to a low of 0.71. The health system's composite score in 2017–2019 was better than the composite target. Of the 34 measures used to calculate the 2019 composite score, 20 were better than internal standardized infection ratio (SIR) targets, seven were between internal targets and SIR of 1.0, and seven were worse than SIR of 1.0. Discussion The Board communicated they find this composite score reporting approach helpful for streamlining their understanding of HAI performance, as compared to traditional approaches of reporting out individual performance measures. Approaches that streamline Board review of quality and safety performance are important as we hold Board members accountable for overseeing quality, seek greater engagement from the Board, and work to minimize measure review overload.

Operating characterization and performance optimization of high-temperature heat pumps: A comparative energy, economic and environmental analysis

The high-temperature heat pump (HTHP) operates under severe conditions and there is a need for further research into its operating characteristics and performance optimization. In this study, the effect of three optimization strategies, namely vapor injection, subcooling and cascade type, on the system characteristics of the HTHP at varying ambient temperatures (Tam) was investigated. Subsequently, a comparative analysis focusing on energy, economy and environment was conducted. As the result shows: The introduction of vapor injection creates the presence of an optimal intermediate pressure and greatly improves the COP of HTHP by a range of 14.7–52.6 %, while the application of an economizer further elevates the COP by 0.6–7.0 %; The cascade cycle exists an optimal intermediate temperature and has operating performance advantages at lower Tam. As the condensing temperature increases from 120 °C to 130 °C to 140 °C, the turning Tam rises from 54 °C to 63 °C to 71 °C, respectively; HTHP requires a certain level of Tam to maintain a higher level of system performance to meet economic and environmental requirements. In the research framework, HTHP begins to show economic advantages at a Tam of 10 °C, while it can only generate benefits of emission reduction at a Tam of 65 °C or higher.

(Invited) Transport Limits for Zinc Aqueous Electrolyte Batteries: Investigation over Multiple Length Scales

Large scale grid level storage would benefit from low cost environmentally sustainable batteries. A system class under investigation is rechargeable zinc anode batteries utilizing aqueous electrolytes. These systems hold promise due to their potential for safe low-cost scalable energy storage. Consideration of the systems over various length scales is warranted due to the complexity of the possible reactions and pernicious parasitic processes. Further, the diversity and intricacies of these battery systems inherently reduce the probability of optimization experiments alone resulting in marketable products.Many of the fundamental issues influencing ion and electron transport and electron transfer and how the transport phenomena evolve under flux are not yet fully undefined. More complete understanding demands multiple characterization approaches used in concert, to tie together information gathered at the local or atomic level and the mesoscale with systems level performance from electrochemical impedance spectroscopy (EIS), galvanostatic cycling (GC), and related techniques. This presentation will provide insight into probes of the reaction mechanisms, evolution of zinc interfaces, methods to determine limitations of cathode function at high rate, and impact of the findings on the electrochemical behavior of the batteries.

High-Performance Lithium-Sulfur Batteries with Atomic V- and Co-Modified Ketjen Black-Sulfur Composite Cathode

Lithium-sulfur (Li-S) batteries are potential alternatives to lithium-ion batteries, which are known to have certain drawbacks. This has drawn special technological attention. Sulfur’s low electrical conductivity, shuttling of the intermediate polysulfides, the slow conversion reaction kinetics of various lithium polysulfides (LiPS), and the major volume change of sulfur in the lithiation reaction are some of the main issues that still need to be resolved before Li-S batteries can be used in practical applications. Additionally, it is likely because there are not enough prognostic models determining energy densities at the cell and pack level based on materials and cell design, most of the articles do not report system-level metrics, specific energy (Wh kg-1), and energy density (Wh L-1).To overcome these problems, atomic vanadium (V) and cobalt (Co) modified ketjen black-sulfur composite (VCKBS) was prepared and used as a cathode in Li-S batteries. The synthesized composite was characterized by various techniques, e.g., XRD, Raman, SEM, HR-TEM, HAADF-STEM, and XPS spectra. The polysulfide adsorption test showed that V had increased the adsorption ability, and cyclic voltammetry displayed the increased catalytic activity resulting from Co, offering a large number of interfacial active sites and ensuring smooth electron transfer. Cycling performance tests showed an initial specific capacity of 1329 mAh g−1, maintained at 1249 mAh g−1 after 100 cycles. Under a higher sulfur loading (2.4 mg cm−2), at 0.2 C, Li-S cells demonstrated an initial specific capacity of 1201 mAh g−1 and retained 985 mAh g−1 after 300 cycles with a low fading rate of 0.059% per cycle. The rate performance tests showed that the prior capacity is nearly recovered, going from 1C back to 0.1C, demonstrating the superiority of the VCKBS material.In addition to the experimental characterization of the Li-S cell performance, energy densities were also predicted by a proposed system-level performance model. The 1st and 100th discharge capacities were used to forecast the system-level specific energies and energy densities. The system-level specific energies and energy densities based on the 100th discharge capacity of VCKBS cathodes had improvements of 1342 and 568%, respectively. This suggests that an easy route to construct the highly stable cathode material may pave the way for the development of highly efficient Li-S batteries. Acknowledgments Hira Fazal acknowledges support from the Türkiye Scholarship/Research Fellowship Program sponsored by the Prime Ministry of Turkey Presidency for Turks Abroad and Related Communities (21PK070917). Damla Eroglu acknowledges support from the Istanbul Development Agency (Award No: TR10/21/YEP/0001). We also thank the National Natural Science Foundation of China (22171180) and the Science and Technology Commission of Shanghai Municipality (20520710400).

Sample-based bounds for coherent risk measures: Applications to policy synthesis and verification

Autonomous systems are increasingly used in highly variable and uncertain environments giving rise to the pressing need to consider risk in both the synthesis and verification of policies for these systems. This paper first develops a sample-based method to upper bound the risk measure evaluation of a random variable whose distribution is unknown. These bounds permit us to generate high-confidence verification statements for a large class of robotic systems in a sample-efficient manner. Second, we develop a sample-based method to determine solutions to non-convex optimization problems that outperform a large fraction of the decision space of possible solutions. Both sample-based approaches then permit us to rapidly synthesize risk-aware policies that are guaranteed to achieve a minimum level of system performance. To showcase our approach in simulation, we verify a cooperative multi-agent system and develop a risk-aware controller that outperforms the system's baseline controller. Our approach can be extended to account for any g-entropic risk measure.

Phase-type distribution models for performance evaluation of condition-based maintenance

ABSTRACT Condition-based maintenance (CBM) is gaining attention due to sensor and cloud-based analytics advancements, but research on its impact on system-level performance is limited. Insufficient understanding during CBM implementation can lead to confidence issues and failures. This study introduces a class of models using phase-type distribution to assess three maintenance strategises: run-to-failure (RTF), time-based preventive maintenance (TBM), and CBM. Employing machine health-index, the framework characterizes production performance by estimating effective process times. The model demonstrates how adjusting CBM thresholds influences process time variations and assesses the impact of changing maintenance frequency for TBM. Applied to a smart cellular manufacturing system, the model shows CBM’s early-stage implementation. Findings indicate CBM with optimized thresholds boosts maximum throughput by 6.77%. Further, CBM achieves an additional 6.84% increase assuming corrective maintenance time can be reduced by 20%. This approach can help manufacturing become smarter through smarter maintenance in the Industry 4.0 era and beyond.

Thermal Energy Storage With Horizontal Thermocline Tank for Sludge Drying Application

Solar thermal technologies can be an attractive option for the decarbonization of process heat applications; in particular, thermal energy storage is a high value proposition for continuous processes that may operate at a range of thermal conditions. A thermal-fluid model is developed to investigate the buoyant flow in a horizontal thermocline storage tank for a sludge-drying application. The process conditions and tank geometry considered are unique compared to the domestic water heating application typically considered in the literature and well suited for parabolic trough collectors. It was found that good separation of hot and cold fluids can be achieved with the long horizontal tank geometry depending on the inlet configuration. Uniform flow distribution along the length of the tank is required to establish a thermocline. Assuming desirable inlet conditions can be achieved, the tank outlet temperature predicted by the thermal-fluid model shows good agreement with the system-level performance model.

Critical evaluation of non-uniform optical phased arrays for real-world beam-steering applications.

Optical phased arrays (OPAs) are a promising technology for the realization of fast and compact non-mechanical optical beam steering. While many experimental demonstrations of integrated OPAs exist in the literature, it is challenging to evaluate their suitability for real-world applications due to the lack of system-level performance requirements. Here, we derive such performance requirements for two of the most promising OPA applications - namely free space optical communications (FSOC) and light detection and ranging (LIDAR) - and show that traditional uniformly spaced OPA architectures likely cannot reach the required performance. In response, we propose the use of non-uniformly spaced OPAs, analyze its performance tradeoffs and show that in certain scenarios they can offer superior performance with decreased complexity.

Impact of Mid-to-Low-Ash, Low-Viscosity Lubricants on Aftertreatment Systems after 210,000-Kilometer Real-World Road Endurance Trials

Engine lubricants globally face the challenge of meeting the demands of new engine technologies while enhancing energy efficiency and reducing emissions. Lubricants must enhance their performance and sustainability, improve reliability in complex and harsh environments, and minimize environmental impact and health risks. This study explores the influence of two different formulations of low viscosity lubricants, tested through actual road endurance trials, on a hybrid vehicle’s aftertreatment system performance and overall emission levels. The study includes 120,000 km of endurance testing in four different challenging environments in China, as well as 90,000 km of endurance testing in a typical urban and highway driving cycle in a large city. Results indicate that emissions from the test vehicles during the 120,000 km and 210,000 km durable Worldwide harmonized Light vehicle Test Cycles (WLTCs) meet China’s Stage 6 light-duty vehicle emission standards, with the 210,000 km Real Driving Emission test (RDE) results also conforming to these standards. Relative to fresh TWC, the light-off temperature increased by a mere 60 °C, and the oxygen storage capacity declined by around 19% following endurance testing. Additionally, the GPF exhibited satisfactory performance after 210,000 km of endurance testing, showing lower backpressure values compared to the fresh-coated samples, with no notable ash buildup observed in the substrate. Drawing on the outcomes of actual road endurance testing, this study illustrates that employing low-to-mid-ash-content, low-viscosity lubricants is both compatible and reliable for aftertreatment systems in present or advanced hybrid technologies. Premium lubricants facilitate vehicles in sustaining compliant and stable emission performance, even amid harsh environments and complex operating conditions. Furthermore, the tested lubricants effectively inhibit excessive aging of the aftertreatment system over prolonged mileage. Moreover, this study discusses the feasibility of rapid aging evaluation methods for aftertreatment systems based on engine test benches, juxtaposed with actual road endurance testing. These findings and conclusions offer crucial references and guidance for enhancing lubricant performance and sustainability. Subsequent studies can delve deeper into the correlation between lubricant performance and environmental impact, alongside optimization strategies for lubricants across various vehicle models and usage scenarios.

Editorial for Special Issue “Advancements in Wireless Communications, Networks, and Signal Processing”

Due to dramatic increases in data traffic over the last decade, there has been growing interest in enhancing system performance levels in data communications and networking [...]

Active optical phased array integrated within a micro-cantilever

Three dimensional sensing is essential in order that machines may operate in and interact with complex dynamic environments. Solid-state beam scanning devices are seen as being key to achieving required system specifications in terms of sensing range, resolution, refresh rate and cost. Integrated optical phased arrays fabricated on silicon wafers are a potential solution, but demonstrated devices with system-level performance currently rely on expensive widely tunable source lasers. Here, we combine silicon nitride photonics and micro-electromechanical system technologies, demonstrating the integration of an active photonic beam-steering circuit into a piezoelectric actuated micro cantilever. An optical phased array, operating at a wavelength of 905 nm, provides output beam scanning over a range of 17° in one dimension, while the inclination of the entire circuit and consequently the angle of the output beam in a second dimension can be independently modified over a range of up to 40° using the piezoelectric actuator.

Computational Method for Optimal Electrolyte Screening Using Bayesian Optimization and Physics Based Battery Model

Lithium-ion batteries (LIBs) powering electric vehicles and large-scale energy storage depend significantly on the composition of liquid electrolyte for optimal performance. We propose a framework coupling Bayesian optimization and physics based battery models to identify electrolytes optimal for specific set of requirements such as less capacity fade and internal heating etc. Our approach is validated through multiple case studies, demonstrating the framework’s efficacy in optimizing electrolyte properties. Additionally, we introduce a deviation index to quantify the proximity of the optimal electrolyte to those in a predefined database. With adaptability to various LIB metrics and battery chemistries, it provides a systematic and efficient approach for screening electrolytes based on system-level performance using physics-based models, contributing to advancements in battery technology for sustainable energy storage systems.

Sustainable freshwater/energy supply through geothermal-centered layout tailored with humidification-dehumidification desalination unit; Optimized by regression machine learning techniques

The application of regression machine learning techniques is crucial for the analysis and optimization of energy systems based on geothermal energy to produce freshwater, power, and heating. This study applied regression machine learning techniques to investigate and optimize a geothermal tri-generation energy system that combines double-flash geothermal energy, humidification-dehumidification desalination, and transcritical carbon dioxide Rankine cycle. The goal was to produce freshwater, power, and heating. The algorithms performed remarkably well, with R-squared values surpassing 96 %. It is worth mentioning that for specific parameters like freshwater production, heating capacity, and efficiency, the R-squared values exceeded an impressive 99 %. The optimum conditions include maintaining a Rankine pressure ratio of 3, a mass flow rate of 30 kg/s, a geothermal temperature of 220 °C, and a turbine pressure ratio of 2.2. By following these ideal parameters, it is possible to achieve the highest level of system performance. This will lead to the production of 7.88 kg/s of freshwater, the generation of 1283 kW of power, a heating capacity of 30.8 kg/s, and an impressive system efficiency of 24.98 %. The findings reveal that the integration of regression machine learning algorithms in geothermal energy systems for freshwater, power, and heating production holds great promise for a sustainable and efficient future.