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At least 397 records · Page 22

Charging Decision Making for Automated Electric Vehicles

Abstract: Overview/Significance With the emerging of autonomous driving and its application in electric vehicles, the charging decision making should be taken over by the vehicles. Autonomous electric vehicles will require the capability to make charging decisions according to the battery energy state, the travel demand and also the available charging infrastructure. The introduction of autonomous driving technology would remove the challenge of co-locating charging infrastructure with driver destinations and presents a driver-free method for EVs to reach nearby charging stations. This will significantly change the charging behavior of electric vehicles. EV driver will no longer need to be present at charging stations for charging actions. Automated EVs can drive to nearby charging stations to perform charging actions by themselves when necessary. Meanwhile, connected vehicles technology makes electric vehicles have the capability to sense and obtain pertinent information from nearby charging station networks and then calculate the corresponding costs and availability for charging. All these promising capabilities bring new opportunities to construct an automatic charging decision making system and improve energy efficiency of charging actions for automatic electric vehicles. Abstract: Methodology This research introduces optimization tools and case studies on charging decision making for automated electric vehicles under personal usage scenario. The designed optimization tools aim to provide charging strategies, i.e. the optimal choice of charging station outside home and the amount of charged energy, by considering constraints from personal daily itineraries and existing charging infrastructure. Abundant real world EV data is utilized to construct stochastic energy consumption prediction model under realistic driving conditions. Advanced dynamic programming technology is utilized to model and solve the potential multi-stage decision making process by considering realistic uncertainties of EV energy cost and dynamics of itinerary information. Large-scale simulation studies using Chicago itinerary data are demonstrated to illustrate energy benefits from automatic charging decision making for future autonomous EVs. Abstract: Results/Conclusions Optimal automatic charging decision making and its energy benefits have been studied for personal automated electric vehicles. A data-driven method based on large amount of real-world data and the corresponding real-time update algorithm have been proposed to construct multi-channel stochastic energy consumption prediction model. Based on the energy cost prediction, dynamic multi-stage charging decision-making models are established for optimal strategies during a daily itinerary. Derived charging strategies can minimize the monetary and energy cost of charging actions for autonomous vehicles. Simulations and case studies show the potential ability of autonomous electric vehicles to reduce the range anxiety and charging infrastructure dependency. Automatic charging decision making can mitigate the pain from electric vehicle charging necessity outside home. In conclusion, automated electric vehicles equipped with an appropriate automatic charging decision making system will help EV driver to relieve from heavy time cost of recharging, reduce the energy cost of performing charging actions and improve the energy efficiency in future electrified transportation system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Automated Mobility Platforms (AMPs) for Versatile, Energy Efficient, Facility and District Scale Transport

The Automated Mobility Platforms (AMPs) concept is envisioned as an on-demand network of automated lightweight electric vehicles serving mobility needs in a large facility or district-scale setting. Supplanting the function of legacy automated people mover systems, AMPs is scalable to meet the needs of moving people in large interior spaces with destinations that are too distant for walking and in which larger motor vehicles would be unfeasible or undesirable. The AMPs system is designed for automated management and operation, extending to how and where the vehicles are sent to serve mobility needs, as organized through a supervisory management system. AMPs vehicles are requested by users via smartphone app or buttons located on interactive infrastructure elements. AMPs vehicles function similarly to elevators, though in the horizontal plane, wherein users summon vehicles, and are moved point-to-point, with user requested destinations set through intuitive interfaces. The concept targets extensibility, manageability, and performance improvements over legacy technologies, with accessibility and safety features integrally designed into the system.

ADA supportive modes↗

Maximizing Efficiency and Quality: Leveraging Automated Testing for Laboratory Commissioning

The traditional commissioning process for a building often implements sampling rates to select equipment for functional acceptance testing when large quantities of equipment are present. While this approach is generally effective in identifying wide-spread issues, it has several key shortfalls. (1) It provides a one-time validation of equipment operation in which the standard documentation is a simple checklist of pass/fail questions. (2) It fails to evaluate equipment not included in the sample rate selection. During the construction and commissioning process of the new Research and Innovation Laboratory (RAIL) in Golden, CO, the National Renewable Energy Laboratory team engaged Group14 Engineering to implement a Connected Commissioning process using fault detection and diagnostic software for automated functional acceptance testing. The goal of this presentation will be to highlight the advantages offered by automated functional testing in this critical laboratory setting. These are primarily (1) sampling 100% of BAS-connected equipment during functional testing, (2) testing results backed by data beyond the traditional pass/fail checklist, and (3) an automated test process that can be regularly executed by the building management team for ongoing commissioning throughout the life of the building. The presentation will also cover technical challenges associated with connected commissioning and the important conversations with the key stakeholders that need to occur well before functional acceptance testing in order to successfully implement the automated testing processes.

automated testing↗

Maximizing Efficiency and Quality: Leveraging Automated Testing for Laboratory Commissioning

The traditional commissioning process uses sampling to select equipment for functional acceptance testing when large quantities of equipment are present. Although this approach is generally effective in identifying wide-spread issues, it has several shortcomings: it fails to evaluate equipment not included in the sample, provides only a one-time validation of equipment operation, and the standard documentation is a simple checklist of pass/fail questions. During the construction and commissioning process of the new Research and Innovation Laboratory (RAIL) in Golden, CO, the National Renewable Energy Laboratory team engaged Group14 Engineering to implement a Connected Commissioning process using fault detection and diagnostic software for automated functional acceptance testing. This presentation highlights the advantages offered by automated functional testing in this critical laboratory setting: (1) sampling 100% of BAS-connected equipment during functional testing, (2) testing results backed by data beyond the traditional pass/fail checklist, and (3) an automated test process that can be regularly executed by the building management team for ongoing commissioning throughout the life of the building. The presentation will also cover technical challenges associated with Connected Commissioning and the important conversations with key stakeholders that need to occur well before functional acceptance testing in order to successfully implement the automated testing processes.

automated testing↗

Challenges and Strategies for Testing Automation Practices at Sandia National Laboratories

Sandia National Laboratories is a premier United States national security laboratory which develops science-based technologies in areas such as nuclear deterrence, energy production, and climate change. Computing plays a key role in its diverse missions, and within that environment, Research Software Engineers (RSEs) and other scientific software developers utilize testing automation to ensure quality and maintainability of their work. We conducted a Participatory Action Research study to explore the challenges and strategies for testing automation through the lens of academic literature. Through the experiences collected and comparison with open literature, we identify these challenges in testing automation and then present strategies for mitigation grounded in evidence-based practice and experience reports that other, similar institutions can assess for their automation needs.

97 MATHEMATICS AND COMPUTING↗

Estimated Bounds and Important Factors for Fuel Use and Consumer Costs of Connected and Automated Vehicles

This report details a study of the potential effects of connected and automated vehicle (CAV) technologies on vehicle miles traveled (VMT), vehicle fuel efficiency, and consumer costs. Related analyses focused on a range of light-duty CAV technologies in conventional powertrain vehicles -- from partial automation to full automation, with and without ridesharing -- compared to today's base-case scenario. Analysis results revealed widely disparate upper- and lower-bound estimates for fuel use and VMT, ranging from a tripling of fuel use to decreasing light-duty fuel use to below 40% of today's level. This wide range reflects uncertainties in the ways that CAV technologies can influence vehicle efficiency and use through changes in vehicle designs, driving habits, and travel behavior. The report further identifies the most significant potential impacting factors, the largest areas of uncertainty, and where further research is particularly needed.

33 ADVANCED PROPULSION SYSTEMS↗

The B737 MAX 8 Accidents as Operational Experiences With Automation Transparency

Automation transparency has come into prominence in the human-machine systems literature, with researchers offering definitions, models, design frameworks, and empirical findings. However, missing from the literature are reflections on the actual operational experiences of human crews interacting with intelligent automation conceived from multiple transparency perspectives. The Boeing 737 MAX 8 accidents present a tragic case of a catastrophic failure of automation transparency. We explore this case with an emphasis on extracting design and regulatory insights for the nuclear power and other safety-critical domains.

99 GENERAL AND MISCELLANEOUS↗

Automated Ride Hailing - Status, Projections, and Critical Safety Review

Automated ride-hailing services, commonly known as 'robo-taxis' are beginning to proliferate and scale. Currently they are available in four major US cities with another 10 cities planning their implementation in the near future. In the US, automated ride-hailing services are dominated by a single provider, with announcements from several competitors of service offerings by end of calendar year 2025. Internationally, only three companies are currently in commercial operations, with many more planned. The scaling of robo-taxi services appears to be the leading application of automated vehicles (AVs), and provides evidence of their anticipated safety in comparison to conventional vehicles. This presentation will provide an overview of the status of deployments of fully operational AVs in ride-hailing services, projections of the number of trips, vehicles, and vehicle miles traveled for the immediate future, and a critical review of the safety data that has been reported, both in the US as well as internationally.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Automated Vehicles in Hazardous Merging Traffic: A Chance-Constrained Approach

To realize the energy efficiency and productivity benefits of automated driving, control algorithms must function safely among conventional vehicles. Prototype tests on public roads have revealed a trend of human-driven vehicles rear-ending automated ones. A popular belief holds that unusually conservative control algorithms play a role in such collisions. In August 2018, an automated vehicle was rear-ended while waiting to merge. Inspired by that incident, this paper examines a resemblant scenario in simulation using model predictive control for the automated vehicle. Constraint setup alternatives to avoid collisions with inattentive following vehicles are proposed and assessed in this simulation environment. In one variant, imminent rear-end collisions are detected and constraints are modified to promote more aggressive merging during such an event. Results show that higher-performing chance constraint designs can reduce collision probability, but may have other adverse effects depending on the particular algorithm.

Dollar, R. Austin↗

Conventional Versus Automated Implantation of Loose Seeds in Prostate Brachytherapy: Analysis of Dosimetric and Clinical Results

Purpose: To review the clinical outcome of I-125 permanent prostate brachytherapy (PPB) for low-risk and intermediate-risk prostate cancer and to compare 2 techniques of loose-seed implantation. Methods and Materials: 574 consecutive patients underwent I-125 PPB for low-risk and intermediate-risk prostate cancer between 2000 and 2008. Two successive techniques were used: conventional implantation from 2000 to 2004 and automated implantation (Nucletron, FIRST system) from 2004 to 2008. Dosimetric and biochemical recurrence-free (bNED) survival results were reported and compared for the 2 techniques. Univariate and multivariate analysis researched independent predictors for bNED survival. Results: 419 (73%) and 155 (27%) patients with low-risk and intermediate-risk disease, respectively, were treated (median follow-up time, 69.3 months). The 60-month bNED survival rates were 95.2% and 85.7%, respectively, for patients with low-risk and intermediate-risk disease (P=.04). In univariate analysis, patients treated with automated implantation had worse bNED survival rates than did those treated with conventional implantation (P<.0001). By day 30, patients treated with automated implantation showed lower values of dose delivered to 90% of prostate volume (D90) and volume of prostate receiving 100% of prescribed dose (V100). In multivariate analysis, implantation technique, Gleason score, and V100 on day 30 were independent predictors of recurrence-free status. Grade 3 urethritis and urinary incontinence were observed in 2.6% and 1.6% of the cohort, respectively, with no significant differences between the 2 techniques. No grade 3 proctitis was observed. Conclusion: Satisfactory 60-month bNED survival rates (93.1%) and acceptable toxicity (grade 3 urethritis <3%) were achieved by loose-seed implantation. Automated implantation was associated with worse dosimetric and bNED survival outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Automated detection of hepatotoxic compounds in human hepatocytes using HepaRG cells and image-based analysis of mitochondrial dysfunction with JC-1 dye

In this study, our goal was to develop an efficient in situ test adapted to screen hepatotoxicity of various chemicals, a process which remains challenging during the early phase of drug development. The test was based on functional human hepatocytes using the HepaRG cell line, and automation of quantitative fluorescence microscopy coupled with automated imaging analysis. Differentiated HepaRG cells express most of the specific liver functions at levels close to those found in primary human hepatocytes, including detoxifying enzymes and drug transporters. A triparametric analysis was first used to evaluate hepatocyte purity and differentiation status, mainly detoxication capacity of cells before toxicity testing. We demonstrated that culturing HepaRG cells at high density maintained high hepatocyte purity and differentiation level. Moreover, evidence was found that isolating hepatocytes from 2-week-old confluent cultures limited variations associated with an ageing process occurring over time in confluent cells. Then, we designed a toxicity test based on detection of early mitochondrial depolarisation associated with permeability transition (MPT) pore opening, using JC-1 as a metachromatic fluorescent dye. Maximal dye dimerization that would have been strongly hampered by efficient efflux due to the active, multidrug-resistant (MDR) pump was overcome by coupling JC-1 with the MDR inhibitor verapamil. Specificity of this test was demonstrated and its usefulness appeared directly dependent on conditions supporting hepatic cell competence. This new hepatotoxicity test adapted to automated, image-based detection should be useful to evaluate the early MPT event common to cell apoptosis and necrosis and simultaneously to detect involvement of the multidrug resistant pump with target drugs in a human hepatocyte environment. - Highlights: > We define conditions to preserve differentiation of selective pure HepaRG hepatocyte cultures. > In these conditions, CYPs, transporters expression and activity were similar to a mixed HepaRG population. > Long term differentiation period before HepaRG hepatocyte isolation influence this establishment. > These conditions were settled to develop a hepatoxicity test using automated-imaging analysis. > JC-1 detects MPT, an early event of cell death, in altered HepaRG hepatocytes when efflux of this dye by MDR1 is inhibited.

60 APPLIED LIFE SCIENCES↗

Automated Quantitative Analysis of Extended Irradiation Defects - Dislocations, Voids and Precipitates in Neutron Irradiated HT-9 Steel

Structural alloys that make up the core components of nuclear reactors are exposed to radiation that can substantially alter the microstructure and mechanical properties of the material. Irradiation can cause the formation of extended defects including dislocation line and loops, voids and various types of precipitates. To understand the irradiation effects, it is critical to characterize these defects individually and collectively to quantify how they evolve throughout irradiation stages. Transmission electron microscopy (TEM) is a standard tool for providing extensive size, number density and spatial distribution of extended irradiation defects, however, manual measurement of defect size and number density requires time-intensive effort to analyze enough defects that provide a statistically meaningful result and are prone to errors of subjectivity. In this work, we developed a set of MATLAB algorithms offering robust and automated identification and quantification of extended irradiation defects like dislocation lines, voids and precipitates commonly observed in neutron irradiated cladding alloys [1]. Using a neutron-irradiated HT-9 martensitic alloy irradiated at 412°C to 111.8 dpa, we demonstrate the capability of these algorithms for quantitative defect analysis. Figure 1 presents defect images of the HT-9 using an advanced diffraction contrast imaging scanning transmission electron microscopy (DCI STEM) that suppresses bend contours and provides better defect contrast compared to conventional TEM [2]. The first step of defect analysis is defect identification, a process that can be digitally achieved by contrast thresholding (for simple defect contrast) and by machine learning computer vision for defect semantic segmentation [3]. Here, labeled binary defect images (Figures 2a and 2c) were used. For dislocation density quantification, we employed an optimized circular-grid intersection method first introduced by Dr. John Steeds [4]. This method is shown in Figures 2a and 2b, where the number of intersections of dislocation lines with circular traces was measured. This produces an unbiased sampling of dislocation lines, regardless of their orientation. This process was optimized with automated digital intersection number and grid length registration. Interestingly, it was found that a relatively large number of circles in a set circular gird is was needed to produce an invariant result (Figure 2b), with a low systematic measurement error. This demonstrates the main advantage of computer-based defect analysis, in performing repetitive operations quickly with a reduced systematic error. For the quantitative analysis of voids and precipitates a challenge encountered with automated defect analysis is feature overlap, particularly when the density of voids/precipitates is high. To mitigate this problem, as shown in Figure 2d, we modified the popular circular Hough transformation and treated ‘circular shape’ as the particle descriptor for voids/precipitates, efficiently resolving the overlapping particles. In summary, this automated digital quantification together with machine learning enabled defect identification [3] opens new opportunities for standardizing the characterization workflow for quantitative analysis of extended irradiation defects.

Sainju, Rajat↗

Automated Radioanalytical System Incorporating Microwave-Assisted Sample Preparation, Chemical Separation, and Online Radiometric Detection for the Monitoring of Total 99Tc in Nuclear Waste Processing Streams

An automated fluidic instrument is described that rapidly determines the total 99Tc content of aged nuclear waste samples, where the matrix is chemically and radiologically complex and the existing speciation of the 99Tc is variable. The monitor links microwave-assisted sample preparation with an automated anion exchange column separation and detection using a flow-through solid scintillator detector. The sample preparation steps acidify the sample, decompose organics, and convert all Tc species to the pertechnetate anion. The column-based anion exchange procedure separates the pertechnetate from the complex sample matrix, so that radiometric detection can provide accurate measurement of 99Tc. We developed a preprogrammed spike addition procedure to automatically determine matrix-matched calibration. The overall measurement efficiency that is determined simultaneously provides a self-diagnostic parameter for the radiochemical separation and overall instrument function. Continuous, automated operation was demonstrated over the course of 54 h, which resulted in the analysis of 215 samples plus 54 hly spike-addition samples, with consistent overall measurement efficiency for the operation of the monitor. A sample can be processed and measured automatically in just 12.5 min with a detection limit of 23.5 Bq/mL of 99Tc in low activity waste (0.495 mL sample volume), with better than 10% RSD precision at concentrations above the quantification limit. This rapid automated analysis method was developed to support nuclear waste processing operations planned for the Hanford nuclear site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data

Mass spectrometry is broadly employed to study complex molecular mechanisms in various biological and environmental fields, enabling 'omics' research such as proteomics, metabolomics, and lipidomics. As study cohorts grow larger and more complex with dozens to hundreds of samples, the need for robust quality control (QC) measures through automated software tools becomes paramount to ensure the integrity, high quality, and validity of scientific conclusions from downstream analyses and minimize the waste of resources. Since existing QC tools are mostly dedicated to proteomics, automated solutions supporting metabolomics are needed. To address this need, we developed the software PeakQC, a tool for automated QC of MS data that is independent of omics molecular types (i.e., omics-agnostic). It allows automated extraction and inspection of peak metrics of precursor ions (e.g., errors in mass, retention time, arrival time) and supports various instrumentations and acquisition types, from infusion experiments or using liquid chromatography and/or ion mobility spectrometry front-end separations and with/without fragmentation spectra from data-dependent or independent acquisition analyses. Diagnostic plots for fragmentation spectra are also generated. Here, in this paper, we describe and illustrate PeakQC’s functionalities using different representative data sets, demonstrating its utility as a valuable tool for enhancing the quality and reliability of omics mass spectrometry analyses.

47 OTHER INSTRUMENTATION↗

Application of DEN refinement and automated model building to a difficult case of molecular-replacement phasing: the structure of a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum

Phasing by molecular replacement remains difficult for targets that are far from the search model or in situations where the crystal diffracts only weakly or to low resolution. Here, the process of determining and refining the structure of Cgl1109, a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum , at ~3 Å resolution is described using a combination of homology modeling with MODELLER , molecular-replacement phasing with Phaser , deformable elastic network (DEN) refinement and automated model building using AutoBuild in a semi-automated fashion, followed by final refinement cycles with phenix.refine and Coot . This difficult molecular-replacement case illustrates the power of including DEN restraints derived from a starting model to guide the movements of the model during refinement. The resulting improved model phases provide better starting points for automated model building and produce more significant difference peaks in anomalous difference Fourier maps to locate anomalous scatterers than does standard refinement. This example also illustrates a current limitation of automated procedures that require manual adjustment of local sequence misalignments between the homology model and the target sequence.

59 BASIC BIOLOGICAL SCIENCES↗

Development and experimental study of an automated laser-foil-printing additive manufacturing system

Purpose This paper aims to present the development and experimental study of a fully automated system using a novel laser additive manufacturing technology called laser foil printing (LFP), to fabricate metal parts layer by layer. The mechanical properties of parts fabricated with this novel system are compared with those of comparable methodologies to emphasize the suitability of this process. Design/methodology/approach Test specimens and parts with different geometries were fabricated from 304L stainless steel foil using an automated LFP system. The dimensions of the fabricated parts were measured, and the mechanical properties of the test specimens were characterized in terms of mechanical strength and elongation. Findings The properties of parts fabricated with the automated LFP system were compared with those of parts fabricated with the powder bed fusion additive manufacturing methods. The mechanical strength is higher than those of parts fabricated by the laser powder bed fusion and directed energy deposition technologies. Originality/value To the best knowledge of authors, this is the first time a fully automated LFP system has been developed and the properties of its fabricated parts were compared with other additive manufacturing methods for evaluation.

Engineering↗

Automated Calibration of Parallel and Distributed Computing Simulators: A Case Study

Many parallel and distributed computing research results are obtained in simulation, using simulators that mimic real-world executions on some target system. Each such simulator is configured by picking values for parameters that define the behavior of the underlying simulation models it implements. The main concern for a simulator is accuracy: simulated behaviors should be as close as possible to those observed in the real-world target system. This requires that values for each of the simulator's parameters be carefully picked, or “calibrated,” based on ground-truth real-world executions. Examining the current state of the art shows that simulator calibration, at least in the field of parallel and distributed computing, is often undocumented (and thus perhaps often not performed) and, when documented, is described as a labor-intensive, manual process. In this work we evaluate the benefit of automating simulation calibration using simple algorithms. Specifically, we use a real-world case study from the field of High Energy Physics and compare automated calibration to calibration performed by a domain scientist. Our main finding is that automated calibration is on par with or significantly outperforms the calibration performed by the domain scientist. Furthermore, automated calibration makes it straightforward to operate desirable tradeoffs between simulation accuracy and simulation speed.

Mc donald, Jesse↗

VAC: A Software Approach to Resilient SCADA Automation

To better secure critical infrastructure, especially power systems, this paper introduces a virtual SCADA automation controller. The automation controller is a gateway into a power subsystem, making it a valuable target for cyber-attacks that could cut it off from the control center and cause a loss of view and control. To prevent this, the Virtual Automation Controller (VAC) is a backup device that mirrors the capabilities of the physical controller. It can communicate via Modbus and DNP3 and is containerized so it can be deployed on a variety of platforms. Furthermore, it utilizes software-defined networking to quickly disconnect a failed automation controller and preserve its state for forensics. The VAC gives system operators time to replace the failed controller and prevents dangerous and costly damage to power systems. The VAC is compared against the SEL 3505-3 RTAC and shown to have the necessary features to act as a failover controller.

Johnson, Jordan↗