Variation In System Performance Research Articles

Designing and multi-objective optimization of a novel multigenerational system based on a geothermal energy resource from the perspective of 4E analysis

Over the past few years, a growing emphasis has been placed on providing sustainable energies to reduce carbon emissions and promote energy efficiency. This paper delved into energy, exergy, exergoeconomic, and exergoenvironmental investigation for a system that combines the Kalina cycle, a double-effect absorption chiller with a vapor compression refrigeration system coupled with an air handling unit driven by a geothermal renewable energy resource. This innovative system generated four distinct outputs: electricity, potable water, cooling load, and hot water. Key system performance variables, such as net power output, coefficient of performance, sum unit cost of the product, energy and exergy efficiencies, the temperature of supply air to the cold store, and potable water production in the base mode, are measured at 63.45 kW, 0.83, 56.74 $/GJ, 62.28 %, 45.67 %, 268.7 K and 20.82 lit/h, respectively. This research explored the impact of various parameters on the output variables, the exergy destruction and environmental impact rate of all components, and the net percent value of the proposed system. The multi-objective optimization significantly improved energy and exergy efficiencies by 6.83 % and 1.8 % from its base mode. Exergy and exergoenvironmental analysis revealed that the highest exergy destruction occurs in Re-injection, and the highest environmental impact rate associated with exergy belongs to the HPG component. Moreover, the geothermal section has the largest share of exergy destruction, approximately 58.5 % of the total exergy destruction of the system.

Miniaturized Antenna Design for Wireless and Powerless Surface Acoustic Wave Temperature Sensors.

This paper presents the introduction, design, and experimental validation of two small helical antennae. These antennae are a component of the surface acoustic wave (SAW) sensor interrogation system, which has been miniaturized to operate at 915 MHz and aims to improve the performance of wireless passive SAW temperature-sensing applications. The proposed antenna designs are the normal-mode cylindrical helical antenna (CHA) and the hemispherical helical antenna (HSHA); both designed structures are developed for the ISM band, which ranges from 902 MHz to 928 MHz. The antennae exhibit resonance at 915 MHz with an operational bandwidth of 30 MHz for the CHA and 22 MHz for the HSHA. A notch occurs in the operating band, caused by the characteristics of the SAW sensor. The presence of this notch is crucial for the temperature measurement by aiding in calculating the frequency shifting of that notch. The decrement in the resonance frequency of the SAW sensor is about 66.67 kHz for every 10 °C, which is obtained by conducting the temperature measurement of the system model across temperature environments ranging from 30 °C to 90 °C to validate the variation in system performance.

Augmenting intensive care unit nursing practice with generative AI: A formative study of diagnostic synergies using simulation-based clinical cases.

As generative artificial intelligence (GenAI) tools continue advancing, rigorous evaluations are needed to understand their capabilities relative to experienced clinicians and nurses. The aim of this study was to objectively compare the diagnostic accuracy and response formats of ICU nurses versus various GenAI models, with a qualitative interpretation of the quantitative results. This formative study utilized four written clinical scenarios representative of real ICU patient cases to simulate diagnostic challenges. The scenarios were developed by expert nurses and underwent validation against current literature. Seventy-four ICU nurses participated in a simulation-based assessment involving four written clinical scenarios. Simultaneously, we asked ChatGPT-4 and Claude-2.0 to provide initial assessments and treatment recommendations for the same scenarios. The responses from ChatGPT-4 and Claude-2.0 were then scored by certified ICU nurses for accuracy, completeness and response. Nurses consistently achieved higher diagnostic accuracy than AI across open-ended scenarios, though certain models matched or exceeded human performance on standardized cases. Reaction times also diverged substantially. Qualitative response format differences emerged such as concision versus verbosity. Variations in GenAI models system performance across cases highlighted generalizability challenges. While GenAI demonstrated valuable skills, experienced nurses outperformed in open-ended domains requiring holistic judgement. Continued development to strengthen generalized decision-making abilities is warranted before autonomous clinical integration. Response format interfaces should consider leveraging distinct strengths. Rigorous mixed methods research involving diverse stakeholders can help iteratively inform safe, beneficial human-GenAI partnerships centred on experience-guided care augmentation. This mixed-methods simulation study provides formative insights into optimizing collaborative models of GenAI and nursing knowledge to support patient assessment and decision-making in intensive care. The findings can help guide development of explainable GenAI decision support tailored for critical care environments. Patients or public were not involved in the design and implementation of the study or the analysis and interpretation of the data.

Experimental study on dynamic characteristics of organic Rankine cycle coupled vapor compression refrigeration system with a zeotropic mixture

The organic Rankine cycle coupled vapor compression refrigeration system is an attractive refrigeration technology that converts low-grade thermal energy into cooling capacity to improve waste heat utilization efficiency. Due to the inevitable change in ambient temperature and cooling demand, the dynamic characteristics of the combined system are worth studying. In this paper, a small experimental apparatus with a common condenser is designed and developed. The dynamic characteristic experiments under different disturbances are carried out to understand the response characteristics of operating parameters and the variation of system performance. The results show that the maximum response time of the system under different disturbances ranges from 493 s to 694 s. The impact of throttle opening on the response characteristics of refrigeration subsystem parameters is significantly higher than that of the organic Rankine cycle. The mass flow rate of organic Rankine cycle has the fastest response to pump frequency, while the compressor inlet temperature changes rapidly with the cooling water temperature. Under a step cooling water temperature, it is important to control the compressor inlet temperature to avoid liquid droplets in its inlet. In addition, the mass flow rate of organic Rankine cycle should be controlled reasonably to achieve the maximum coefficient of system performance. The cooling capacity of the system is mainly affected by the cooling water temperature and the throttle valve opening. During the experiment, the maximum cooling capacity and performance coefficient of the system are 3.75 kW and 0.275, respectively. This work can provide guidance for the design of the control strategy of the combined system.

Performance evaluation of photovoltaic-phase change material-thermoelectric system through parametric study

The dual-directional photovoltaic-thermoelectric generator (PV-TEG) system offers higher performance. However, there may be scenarios where the PV and TEG devices receive different levels of irradiation, leading to variations in performance. Under these conditions, the impact of using a PCM heat sink on the system's thermal management effectiveness has not yet been clearly established. Given these considerations, this study builds a coupled heat transfer-laminar flow-electromagnetic numerical model to explore the variations in system performance when subjected to different radiation intensities. The investigation also explores the implications of integrating PCM with varying thicknesses and melting points. Based on the obtained data, it can be concluded that when the PV and TEG devices are exposed to different radiation intensities, the system exhibits distinctly different performance. The highest power output and conversion efficiency are more than 0.16 W and 16 % for the PV device, and 0.08 W and 1 % for the TEG device. Furthermore, using thicker PCM allows the PV and TEG devices to maintain higher output power and efficiency for a longer period, surpassing the performance of systems with thinner PCM. Moreover, the PCM with a melting point of 301.15K has demonstrated the best potential for thermal management in the PV-TEG system.

Design of an Iterative Method for MapReduce Scheduling Using Deep Reinforcement Learning and Anomaly Detection

Due to high complexities within distributed computing environments, there's a critical need for advanced scheduling frameworks that are capable of optimizing MapReduce systems. Current approaches have static policies that limit their capability to adapt to changing system dynamics and workload variations for different cloud scenarios. To overcome these issues, this study introduces a robust MapReduce framework empowered by intelligent scheduling algorithms, tailored to enhance system efficiency and resilience levels. The framework introduces three novel scheduling models: Deep Reinforcement Learning for Dynamic Job Scheduling (DRDJS), Anomaly Detection-driven Adaptive Scheduling (ADAS), and Cluster-based Job Categorization and Scheduling (CJCS). DRDJS utilizes deep reinforcement learning to dynamically generate optimal scheduling policies based on multiple metrics that include historical job data, system metrics, and workload characteristics. This adaptive approach leads to significant reductions in job completion times, outperforming static scheduling methods by up to 30%. Next, ADAS leverages anomaly detection to prioritize critical tasks and efficiently allocate resources in response to anomalies, resulting in a notable improve scheduling speed by up to 40%. Finally, CJCS employs clustering algorithms to categorize jobs based on their resource requirements and execution profiles, enabling more accurate resource allocation and reducing average job completion times by up to 25%. By integrating these methods into a unified scheduling framework, the proposed solution addresses the variability in job characteristics and system performance, thereby enhancing the overall throughput and stability of MapReduce operations.

Investigation of a new holistic energy system for a sustainable airport with green fuels

The advancement of sustainable solutions through renewable and clean energy sources is considered crucial to mitigate carbon emissions. This study reports a novel system developed for an airport utilizing geothermal, biomass, and PV solar energy sources. The proposed system is capable of producing five useful outputs, including electrical power, hot water, hydrogen, kerosene, and space heating. The system proposed in the study is further considered for the Vancouver Airport in British Columbia, Canada using the most recent available data. The geothermal sub-system introduced in this study is also unique, which utilizes the carbon dioxide captured from biomass gassification as the heat transfer medium for geothermal heat to the Rankine cycle for power generation and heating. The present system is modeled and analyzed using thermodynamic method through energetic and exergetic approaches to determine the variation in system performance based on different annual environmental conditions. The biomass gasification and kerosene production are evaluated based on the Aspen Plus models and simulation. The efficiencies of the geothermal system with the carbon dioxide reservoir are found to have energetic and exergetic efficiencies of 78% and 37% respectively. The total hydrogen production is potentially estimated to be 452 tons on an annual basis. The kerosene production mass flow rate is reported as 0.112 kg/s. The overall energetic and exergetic efficiencies of the system are found to be 41.8% and 32.9% respectively. Moreover, this study offers crucial information for the aviation sector to adopt sustainable solutions more effectively.

Performances of constructed wetland system to treat whey and dairy wastewater during a macrophytes life cycle

Constructed wetlands system (CWs) have been proposed as an economical, efficient and sustainable wastewater treatment technology. The aim of this paper was to provide the first published data on the efficiency of CWs for dairy wastewater treatment in Tunisia. In most CWs, good organic, total suspended solids (TSS) and nutrient removal was measured. In order to evaluate the efficiency of this process, hybrid small-scale wetland system was designed containing three horizontal subsurface flow (HSSF) and one free water surface flow (FWS). A mixture of Reeds (Phragmites australis), Cattails (Typha latifolia), and Papyrus (Cyperus papyrus) was planted. Several water quality parameters in both raw and treated wastewaters were monitored during the macrophytes life cycle. The average influent properties for 20 % of whey are: TSS (3040 mg/L), COD (5060 mg O2/L), BOD5 (3020 mg O2/L), TKN (79 mg N/L) and TP (32,2 mg P/L). Removal efficiencies of 99.6 % for TSS, 80 % for COD, 97 % for BOD5, 90.4 % for TKN and 99.6 % for TP were observed. The results reveal temporal variations in system performance according to macrophyte growth rates. Reeds, Cattails and Papyrus start their life cycle at the beginning of the winter and continue growing in summer. The effluent pH, TSS, COD,BOD5, TKN and TP concentrations were in compliance with both irrigation reuse and discharge regulations.

Inventory management practices and performance of electoral systems in Kenya

Effective inventory management plays a pivotal role in the overall performance and functionality of systems across various sectors. In the context of electoral systems, where precision, efficiency, and transparency are paramount, the management of inventory, including the planning, tracking, and control of resources, is of utmost importance. Therefore, the study sought to determine the role of inventory management practices on the performance of electoral systems in Kenya. The research design that was used in this study was a longitudinal research design. The population for this study consisted of 373 Commission Secretary/Chief Executive Officer (CS/CEO), Deputy Commission Secretary (DCS), Directors, Managers, County Election Managers, and Constituency Election Coordinators within 290 constituencies of Kenya's August 2017 election. A total of 373 respondents were used as the sample size for the study. Data was used as primary and secondary. While self-administered questionnaire and interview guide were used to collect primary data, the study reviewed the previous evaluation reports to seek the secondary data on General election performance. The data was collected and then analyzed by both descriptive and inferential statistical tools. Being that the study dealt with the relationship study, the study therefore used a regression model as a tool of analysis and the results that were generated were presented in the form of tables. The results of this study benefited policy makers, managers, administrators, citizens all whole, researchers, consultants, scholars, and trainers involved in Election Administration. This study tested the null hypotheses that inventory management practices had no significant role in the performance of electoral systems in Kenya. Pragmatism paradigm approach and mixed method research were adopted in this study. The questionnaire tested both validity and reliability. Quantitative and qualitative techniques were used to analyze the collected data with the assistance of Statistical Package for Social Sciences (SPSS) software version 25. Multiple regression and correlation analysis were carried out. The regression analysis results demonstrated a strong and significant role of inventory management practices on the performance of electoral systems. The R-squared values indicated that approximately 79% of the variation in electoral system performance was explained by inventory management practices. The adjusted R-squared value of 0.788 accounted for the number of predictors in the model. In conclusion, the study reveals that efficient inventory management practices significantly influence the performance of electoral systems in Kenya, emphasizing the need for standardized handling, storage, and transportation processes, the adoption of technology-driven monitoring systems, centralized inventory management, just-in-time approaches, regular cycle counting, and continuous improvement efforts. However, there remains unexplained variance in performance, warranting further investigation to identify additional influential factors. Additionally, future research should extend its focus to other countries in the East African region to comprehensively assess inventory management practices and their impact on electoral system performance

Cooling and dehumidification performance study of a new air conditioning system with double evaporation temperature

In order to improve the cooling and dehumidification performance of household air conditioners, a new air conditioning system with double evaporation temperature is proposed. The simulation model of the new system is established, the variation of system performance with compressor high/low pressure cylinder volume ratio, inlet air temperature, relative humidity, air speed, etc. are simulated and experimentally studied. The research results show that when the volume ratio of high and low pressure cylinders of compressor is 0.5∼1.2 and air speed 2.2 m/s, cooling COP of double evaporation temperature air conditioning system could obtain the maximum value. Compared with single evaporation temperature system, cooling COP of double evaporation temperature system can be increased 3%∼4.2%; the dehumidification capacity is 0.06∼0.61kg/h, about 1.69%∼5.83% higher.

BenchFaaS: Benchmarking Serverless Functions in an Edge Computing Network Testbed

The serverless computing model has evolved as one of the key solutions in the cloud for fast autoscaling and capacity planning. In edge computing environments, however, the serverless model is challenged by the system heterogeneity and performance variability. In this paper, we introduce BenchFaaS, an open-source edge computing network testbed which automates the deployment and benchmarking of serverless functions. Our edge computing network considers a cluster of virtual machines and Raspberry Pis, and is designed to benchmark serverless functions under different hardware and network conditions. We measure and evaluate: (i) overhead incurred by testbed, (ii) performance of compute intensive tasks, (iii) impact of application payload size, (iv) scalability, and (v) performance of chained serverless functions. We share the lessons learnt in engineering and implementing the testbed. We present the measurement results and analyze the impact of networked infrastructure on serverless performance. The measurements indicate that a properly dimensioned edge computing network can effectively serve as a serverless infrastructure.

A Multi-Objective Time – Series Optimization for Optimum Planning Design of Integrative Power System with the Effects of Multi-Dimensional Sources of Uncertainty

Time series aggregation (TSA) procedures are used to simplify data entry and enhance solution efficiency. This study suggested a two-step multi-objective optimization framework for TSA strategy determination. TSA methodologies for optimum MES design and operation were used to create the multi-energy system’s preliminary design. In the second step, the system’s total annual cost, as well as loss of load probability (LSLP), were used as objectives, or the optimal combination of the several objectives was found optimal TSA strategy for the MES’s structure and performance. The ideal energy-storage MES design proved the method’s efficacy. TSA techniques were compared and analyzed for architectural schemes & system performance variations. The findings show that the initial full-time series data may be used to verify the viability of the best MES design schemes and quantify the departure of outcomes from alternative TSA procedures. LSLP decrease raises expenses. The TAC of the framework improves from $9.79 × 107 to $1.56 × 108 when the LSLP reduces to 7.90% to zero in the numerous grids method (TG1) with 730-time steps (TS). To fulfill energy system demand, the minimal LSLP approach must be chosen. The best TSA tactics for MES design may be chosen based on unique needs.

SARS-CoV-2 infection reduces quality of sperm parameters: prospective one year follow-up study in 93 patients.

Short- and long-term implications of SARS-CoV-2 on the quality of the sperm and the results of this on fertility remain largely unknown due to lack of longitudinal studies. In this longitudinal observational cohort study, we aimed to analyse the differential effect and the impact of SARS-CoV-2 infection on different semen quality parameters. Sperm quality was assessed using the World Health Organization criteria, DNA damage to sperm cells by quantifying the DNA fragmentation index (DFI) and the high-density stainability (HDS), IgA- and IgG-anti-sperm antibodies (ASA) were assessed with light microscopy. SARS-CoV-2 infection was associated with sperm parameters that were independent of spermatogenic cycle like progressive motility, morphology, DFI and HDS, as well as spermatogenic cycle dependent parameters such as sperm concentration. Detection of IgA- and IgG-ASA allowed classification of patients in three different groups according to its sequence of appearance in sperm during post-COVID-19 follow-up. The maximum progressive motility was lowest during follow-up in patients without ASA (41.9%), intermediate in patients with only IgA-ASA (46.2%) and highest inpatients who had both IgA- and IgG-ASA (54.9%). SARS-CoV-2 infection was associated with changes of all analysed sperm parameters to a different degree which is also observed in their return to normality and is suggestive of individual variations in the patient's immune system performance. Firstly, sperm production is decreased through temporal immune mediated arrest of active meiosis, and secondly immune induced sperm DNA damage prevents fertilization if transferred to the oocyte. Both mechanisms are temporal, and most sperm parameters return to baseline after infection. AML (R20-014), Femicare.

Dynamic characteristics of a mechanically coupled organic Rankine-vapor compression system for heat-driven cooling

There are large quantities of compression heat wasted and cooling capacity required in cryogenic air separation units (ASUs). Mechanically coupled organic Rankine-vapor compression (ORVC) system is an attractive technology to realize heat-driven refrigeration for compression heat recovery and compression power saving in cryogenic ASUs. As the states of the compression heat inevitably change with the ambient environment, off-design operation of the ORVC system is worth investigating. A mechanically coupled ORVC test bench is designed and built in this paper. Off-design experiments are carried out to figure out the dynamic response characteristics and system performance variations. Results show that, the ORC working fluid flowrate and the opening of the throttle valve are the key operation parameters affecting the system dynamic response. The experimental system responds quickly with delay time less than 10 s and response time less than 1 min. The opening of the throttle valve has the greatest impact on the cooling capacity and system COP which reaches up to 0.61. This research may provide reference for control scheme design and actual operation for the compression heat recovery system in cryogenic ASUs.

Single leg drop jump is affected by physical capacities in male soccer players following ACL reconstruction

ABSTRACT Single leg drop jump (SLDJ) assessment is commonly used during the later stages of rehabilitation to identify residual deficits in reactive strength but the effects of physical capacity on kinetic and kinematic variables in male soccer players following ACL reconstruction remain unknown. Isokinetic knee extension strength, kinematics from an inertial measurement unit 3D system and SLDJ performance variables and mechanics derived from a force plate were measured in 64 professional soccer players (24.7 ± 3.4 years) prior to return to sport (RTS). SLDJ between-limb differences was measured (part 1) and players were divided into tertiles based on isokinetic knee extension strength (weak, moderate and strong) and reactive strength index (RSI) (low, medium and high) (part 2). Moderate to large significant differences between the ACL reconstructed and uninjured limb in SLDJ performance (d = 0.92–1.05), kinetic (d = 0.62–0.71) and kinematic variables (d = 0.56) were evident. Stronger athletes jumped higher (p = 0.002; d = 0.85), produced greater concentric (p = 0.001; d = 0.85) and eccentric power (p = 0.002; d = 0.84). Similar findings were present for RSI, but the effects were larger (d = 1.52–3.84). Weaker players, and in particular those who had lower RSI, displayed landing mechanics indicative of a ‘stiff’ knee movement strategy. SLDJ performance, kinetic and kinematic differences were identified between-limbs in soccer players at the end of their rehabilitation following ACL reconstruction. Players with lower knee extension strength and RSI displayed reduced performance and kinetic strategies associated with increased injury risk.

Effect of Merit System and Work Achievement on Employee Competence at PT Purnatarum Murni Rahayu Bandung

Purnatarum Murni Rahayu is engaged in providing Liquid Petroleum Gas (LPG) services for the Greater Bandung area, as a company that functions as storage, the employees are required to have good competence, this is related to employee performance and employee recruitment planning. This study aims to determine whether the merit system variable has a significant effect on employee competence and whether work performance has a significant effect on employee competence. The research method used is descriptive, verification, namely by describing each variable and testing the three variables with a quantitative (statistical) approach which is then analyzed and compared with existing theories and problems to conclude. Simultaneously the magnitude of the effect of the merit system and work performance is 67.4% on competence while other factors are not examined (epsilon) but affect competence at 33.6%. The results of the study which are based on the partial hypothesis state that the merit system and work performance variables can be detected from the magnitude of the influence of each factor consisting of the merit system factor (X1of32.1%, work performance factor (X235) of,5%, to the competence of employees at PT. Purnatarum Murni Rahayu. This study concludes that the merit system has an effect on employee competence and work performance has a more dominant influence on employee competence than the merit system

Productivity augmentation of a solar distiller utilizing a wire mesh absorber with a pulsed flow regime

This work introduces an experimental study on the possibility of using the metal wire mesh as a packed absorber (SS-WM) with pulsed water flow to enhance the performance of the solar distiller experimentally. The utilization of a wire mesh increases the absorptive surface area over the traditional absorber. The experimental model was designed, manufactured, and tested under actual climatic conditions. Numerous system performance variables, including sprayer feed water flow rate (FWFR), pulsed water flow operation frequency, and packed absorber parameters (size and number of wire mesh layers), were evaluated based on thermodynamic, economic, and water production assessments. Results show that the packed absorber in SS-WM enhances thermal energy absorption and storage. The water yield is enhanced by about 102 % by using the small size of wire mesh and 30 % and 41 % for medium and large sizes, respectively. The best performance enhancement of SS-WM is reached by using two layers with enhancement in the water yield, average thermal efficiency, and cost by about 102 %, 102 %, and 44 %, respectively, compared to traditional design. The water yield, average thermal efficiency, and freshwater cost are about 3.007 l/d, 45 %, and 0.008 USD/l respectively.

Leveraging Code Snippets to Detect Variations in the Performance of HPC Systems

Variations in the performance of parallel and distributed systems are becoming increasingly challenging. The runtimes of different executions can vary greatly even with a fixed number of computing nodes. Many HPC applications on supercomputers exhibit such variance. This not only leads to unpredictable execution times, but also renders the system’s behavior unintuitive. The efficient online detection of variations in performance is an open problem in HPC research. To solve it, we propose an approach, called <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vSensor</small> , to detect variations in the performance of systems. The key finding of this study is that the source code of programs can better represent performance at runtime than an external detector. Specifically, many HPC applications contain code snippets that are fixed workload patterns of execution, e.g., the workload of an invariant quantity and a linearly growing workload. This observation allows us to automatically identify these snippets of workload-related code and use them to detect variations in performance. We evaluate <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vSensor</small> on the Tianhe-2A system with a large number of parallel applications, and the results indicate that it can efficiently identify variations in system performance. The average overhead of 4,096 processes is less than 6% for fixed-workload v-sensors. We identify a problematic node with slow memory by using <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vSensor</small> that degrades the performance of the program by 21%. A serious issue with network performance is also detected that slows down the Tianhe-2A system by 3.37 times for an HPC kernel.

Semi-autonomous bus platooning service optimization with surrogate modeling

Autonomous driving holds great promise for easing the driver shortage issue that has occurred in many countries. In this paper, we consider a semi-autonomous transit system where (1) individual buses could form platoons to increase bus capacity during peak hours and operate separately during off-peak hours; and (2) buses may drive autonomously in certain geofenced areas yet need to be guided by human drivers elsewhere (e.g., SAE level 4, semi-autonomous). We model buses driving autonomously within the geofenced area as short-turn bus service, and jointly optimize bus dispatch headway, platoon size and service type through an integer programming model to address the driver shortage issue. The proposed model considers real-world and micro-level bus operation processes for mixed traffic of short-turn and full route buses, with bus fleet and driver workforce constraints being modeled endogenously. Since the model is non-linear, we further develop a radial basis function-based surrogate framework to solve the model efficiently. Experimental results show that, compared to the conventional bus service that uses fixed bus capacity only, semi-autonomous bus platooning service reduces operation cost significantly while reducing passenger wait time. System performance variations of the proposed model under different driver availabilities are also examined.

FSVPy: A python-based package for fluorescent streak velocimetry (FSV)

Predictive constitutive equations that connect easy-to-measure transport properties (e.g., viscosity and conductivity) with system performance variables (e.g., power consumption and efficiency) are needed to design advanced thermal and electrical systems. In this work, we explore the use of fluorescent particle-streak analysis to directly measure the local velocity field of a pressure-driven flow, introducing a new Python package (FSVPy) to perform the analysis. Fluorescent streak velocimetry combines high-speed imaging with highly fluorescent particles to produce images that contain fluorescent streaks, whose length and intensity can be related to the local flow velocity. By capturing images throughout the sample volume, the three-dimensional velocity field can be quantified and reconstructed. We demonstrate this technique by characterizing the channel flow profiles of several non-Newtonian fluids: micellar Cetylpyridinium Chloride solution, Carbopol 940, and Polyethylene Glycol. We then explore more complex flows, where significant acceleration is created due to microscale features encountered within the flow. We demonstrate the ability of FSVPy to process streaks of various shapes and use the variable intensity along the streak to extract position-specific velocity measurements from individual images. Thus, we demonstrate that FSVPy is a flexible tool that can be used to extract local velocimetry measurements from a wide variety of fluids and flow conditions.