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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 667 records · Page 37

Diesel Engine Waste Heat Driven Absorption Heat Pumps for ECU Applications in Defense Installations

A thermally activated absorption heat pump suitable for use in naval expeditionary Environmental Control Units, as well as residential space-conditioning, is developed. Waste heat characteristic of the exhaust stream from a diesel engine GenSet is used to drive an absorption cycle to provide cooling. The heat source is coupled to the heat pump using an intermediate fluid loop for flexible deployment. With minor modifications, the heat pump could also provide heating at high coefficients of performance, resulting in versatile functionality. This technology capitalizes on heat and mass transfer enhancement possible in microscale passages to provide a compact architecture for the components and the overall system. The working fluid pair with zero Global Warming Potential is contained within this assembly, reducing fluid inventories significantly over conventional systems. Quiet, reliable, long-life operation due to the absence of a compressor and the use of few moving parts are further critical distinguishing advantages. Modularity in cooling capacity has been demonstrated through scaling-up of component geometry and internal features and dimensions. The core technology was initially demonstrated with a proof-of-concept microscale absorption chiller measuring 200 × 200 × 34 mm and weighing 7 kg that delivered 300 W of cooling in laboratory tests. In the previous BEETIT project, the team made significant advances over the proof-of-concept. System and component designs with > 10× scale-up in capacity were developed, in a packaged unit capable of standalone operation with a semi-autonomous control system. A cooling capacity of 3.5 kW with a COP > 0.5 at an ambient temperature of 35°C was demonstrated for this natural gas-fired unit. Significant cost reductions in fabrication were achieved using low-cost brazing instead of diffusion bonding. In companion projects funded by the Southern Company and the Georgia Research Alliance, stamping and fluid forming techniques were investigated to fabricate microscale features instead of photochemical etching, thereby leading to significant cost reductions. In a follow-on effort funded by ARPA-E and NAVFAC, a 2.7 kW cooling unit was developed to provide cooling at a severe ambient condition of 51.7°C. The unit was driven directly by diesel engine exhaust heat. Innovative finned heat and mass exchangers for the ambient-coupled condenser and absorber were developed. In the present effort, a standalone, packaged and controllable 10.5 kW cooling capacity absorption chiller is developed. This demonstrates a 30× scale up from the proof-of-concept, thus validating the scalability of microchannel heat exchangers for absorption heat pumps. Autonomous operation algorithms demonstrated enhanced dynamic performance. The knowledge from previous projects was leveraged to develop novel component designs that further helped in miniaturizing the heat exchangers. All coupling fluids are hydronically coupled to aid flexible field deployment. The prototype unit provides design cooling capacity at high ambient temperature conditions of 44°C at COP > 0.6.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Key factors in designing a robust biorefinery feedstock preprocessing system

One essential prerequisite for achieving design throughput and product conversion yield of cellulosic biofuel in commercial operation is a robust biomass feedstock preprocessing system. Such a system will reliably and steadily supply consistent quality feedstock to the conversion reactor. Pioneer cellulosic biofuel plants have encountered many feedstock handling challenges which lead to lengthy startup and difficulties in meeting plant nameplate production rate. Most of the biomass material handling challenges are caused by: (1) variability in biomass properties especially for herbaceous materials such as corn stover, (2) inadequate integrated testing of equipment, (3) not using the appropriate equipment or equipment design for the job, (4) mismatching of equipment capacity and turn down ratio, (5) lack of integrated control for the whole feedstock preprocessing system, and (6) inadequate surge capacity. This presentation will discuss the feedstock preprocessing challenges, identify key areas from equipment design and operation to process integration requiring optimization or further development to achieve robust integrated biomass feedstock preprocessing systems.

09 BIOMASS FUELS↗

Quantifying Energy Justice Goals in the Power Sector: Developing and Using Metrics

New policy goals are explicitly guiding the future grid toward greater energy equity. At the same time, policy goals also guide the grid toward decarbonization and resilience, while maintaining cost, security, and reliability cornerstone requirements. In conclusion, these pressures create a dilemma: moving urgently to address climate change and respond to energy disruptions, but also slowly to engage communities on the climate frontlines in earnest.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Long-Term Impacts of Constrained Transmission Deployment on the Cost-Reliability Tradeoff

Traditional Resource Adequacy (RA) frameworks in the U.S. undervalue the contributions of inter-regional transmission to resource adequacy during stress periods, focusing on the availability of nameplate capacity instead. However, availability of nameplate capacity does not always translate into electricity delivery, especially during tail events. Moreover, the rapid deployment of energy-limited resources and increasing electricity demand challenge existing resource adequacy frameworks and couple regional electricity demand and availability of supply via transmission. We propose a two-stage framework that goes beyond the existing capacity-centered approaches to reveal the RA contributions of transmission. In the first stage we introduce a multi-objective optimization framework to quantify the merits of transmission expansion via Pareto Frontiers under alternative futures of no transmission investment, primary energy resources availability and demand growth. The second stage focuses on tail events and leverages the results of the first stage to characterize the risk profile of regional consumers across the U.S. under the alternative energy futures. We find that no new transmission can lead to a more expensive and less reliable national grid across scenarios, however, the impact on regional RA can vary. The probabilistic analysis reveals that transmission investments can alleviate the tail risk of consumers, however, the availability of fuel resources does not always alleviate regional tail risks. Our findings inform policymakers and utilities on the prioritization of transmission investments to mitigate the risk of widespread outages, also for tail events, and ensure reliable and affordable electricity delivery to all.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Solving Unit Commitment Problems with Demand Responsive Loads

This work focuses on using variations of the Frank-Wolfe (FW) algorithm for solving unit commitment problems with high volumes of demand responsive loads on the power grid. We present a formulation of the unit commitment problem with demand responsive loads. We then show through reformulation and relaxations of the problem that variations of the Frank-Wolfe algorithm can be used to determine the time series decisions for the demand responsive loads. We show through computational experiments on the IEEE Reliability Test System that the timeseries of demand responsive load decisions obtained through our approach are near optimal and describe how large-scale parallel implementations of our approach can be highly computationally efficient.

demand response↗

Assessing the benefits of capacity payment, feed‐in‐tariff and time‐of‐use programme on long‐term renewable energy sources integration

Recently, demand response programmes (DRPs) have captured great attention in electric power systems. DRPs such as time‐of‐use (ToU) programme can be efficiently employed in the power system planning to reform the long‐term behaviour of the load demands. The composite generation expansion planning (GEP) and transmission expansion planning (TEP) known as composite GEP–TEP is of high significance in power systems to meet the future load demand of the system and also integrate renewable energy sources (RESs). In this regard, this study presents a dynamic optimisation framework for the composite GEP–TEP problem taking into consideration the ToU programme and also, the incentive‐based and supportive programmes. Accordingly, the performances of the capacity payment and feed‐in tariff mechanisms and the ToU programme in integrating RESs and reducing the total cost have been evaluated in this study. The problem has been formulated and solved as a standard two‐stage mixed‐integer linear programming model aimed at minimising the total costs. In this model, the ToU programme is applied and the results are fed into the expansion planning problem as the input. The proposed framework is simulated on the IEEE Reliability Test System to verify the effectiveness of the model and discuss the results obtained from implementing the mentioned mechanisms to support the RESs integration.

Javadi, Mohammad Sadegh↗

Detection of False Data Injection Attacks in Battery Stacks Using Input Noise-Aware Nonlinear State Estimation and Cumulative Sum Algorithms

Grid-scale battery energy storage systems (BESSs) are vulnerable to false data injection attacks (FDIAs), which could be used to disrupt state of charge (SoC) estimation. Inaccurate SoC estimation has negative impacts on system availability, reliability, safety, and the cost of operation. In this article a combination of a Cumulative Sum (CUSUM) algorithm and an improved input noise-aware extended Kalman filter (INAEKF) is proposed for the detection and identification of FDIAs in the voltage and current sensors of a battery stack. The series-connected stack is represented by equivalent circuit models, the SoC is modeled with a charge reservoir model and the states are estimated using the INAEKF. Further, the root mean squared error of the states’ estimation by the modified INAEKF was found to be superior to the traditional EKF. By employing the INAEKF, this article addresses the research gap that many state estimators make asymmetrical assumptions about the noise corrupting the system. Additionally, the INAEKF estimates the input allowing for the identification of FDIA, which many alternative methods are unable to achieve. The proposed algorithm was able to detect attacks in the voltage and current sensors in 99.16% of test cases, with no false positives. Utilizing the INAEKF compared to the standard EKF allowed for the identification of FDIA in the input of the system in 98.43% of test cases.

25 ENERGY STORAGE↗

Linking Transient Voltage to Spatially-Resolved Luminescence Imaging to Understand Reliability of Perovskite Photovoltaics

In this work, we present a methodology to separate effects of perovskite device metastability from irreversible degradation, using stress/rest cycling under constant current bias while collecting a series of electroluminescence images and continuously monitoring voltage. We develop a simulation model and procedures for image processing to better understand the effects of ion parameters on the transient nature of voltage and evolving electroluminescence images.

electroluminescence↗

Enhancing Operational Safety via Agentic Dialogue Hazard Identification Analysis

Operational safety in high-stakes domains such as industrial process control, autonomous, and safety-critical systems demand reliable hazard identification. While large language models (LLMs) have shown promise in automating safety analysis tasks, single-turn, monolithic inference is brittle: it lacks the self-correction, deliberation, and contextual refinement that safety engineers apply iteratively. In this paper, we introduce HAZDIAL, a framework that investigates whether structured agentic dialogue (multi-agent, multi-turn interactions) improves the quality of NLP-based hazard identification over single-pass baselines. We systematically compare two dialogue modalities: adversarial debate and constructive discussion, and propose an genetic algorithm-based agentic interaction optimization. We evaluate all configurations against a curated golden dataset using standard classification metrics (accuracy, precision, recall, F1) and a novel dialogue metrics. This work advances the intersection of dialogue systems, multi-agent reasoning, and AI safety, providing empirical evidence for dialogue-driven hazard analysis.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗

Off-Road Vehicles Research Workshop (Summary Report)

This report summarizes the off-road vehicles stakeholder workshop that was focused on research, technical challenges, and future direction related to off-road vehicles and held at Argonne National Laboratory in October 2018. The views expressed in this report are those of the workshop participants. Topics discussed and included in this report are engine efficiency and emissions; efficient fluid power; and system integration, control, and new technologies. The purposes of this workshop were to: 1) Discuss and exchange information on the current state of technology for off-road vehicles; 2) Work collectively to address the technical challenges; and 3) Help shape the future direction for off-road vehicles research and development (R&D). The report highlights some key points, takeaways, and technical challenges and ideas to inform DOE R&D programs for the off-road sector. The workshop objectives were to: • Identify the barriers to cost-effective, high-efficiency, off-road vehicles; • Identify pre-competitive research topics that could have the biggest impact in overcoming barriers; and • Identify metrics that should be applied to program progress and ambitious but realistic goals. Customer acceptance, reliability, and system durability are some of the market barriers to new technology that were discussed during the workshop. Participants agreed that a comprehensive strategy is required to explore ways to improve engine efficiency while lowering emissions (i.e., NO x , GHG, etc.) and at the same time, meet customer needs and expectations. A full system optimization was recommended for off-road vehicles. It was noted that off-road vehicles are very diverse with a wide range of engine size and vehicle applications. A need for R&D for transient operations and other operating conditions was identified, as off-road vehicles are currently optimized for steady state. Fuel type for these vehicles has an important role. Fuel cost and fuel delivery to the work-site are challenging for any new fuel. Increased vehicle electrification is one of the new technologies discussed during the workshop. Electric propulsion for off-road vehicles has limited applications in the near term, but hybridization seems more promising. Furthermore, electrification requires better batteries and, possibly, the use of higher-voltage systems. Developing more efficient component technologies, including pumps, motors, and valves, is important for more efficient fluid power systems. New work-circuit architectures that can decrease throttling losses and better integrate the work circuit and engine can offer significant efficiency gains. Autonomous vehicles for off-road sectors were also discussed. Autonomous vehicles for off-road space are very appealing for some markets due to shortage in skilled labor and its significant impact on productivity, vehicle weight, and therefore, energy use and emissions. Autonomous driving for mining and farming applications is more feasible because the routes are predefined, but for other applications, such as forestry and construction vehicles, autonomous driving would be very challenging.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Unreliable Sustainable Infrastructure: Three Transformations to Guide Cities towards Becoming Healthy 'Smart Cities'

The term 'leapfrogging' has been applied to cities and nations that have adopted a new form of infrastructure by bypassing the traditional progression of development, e.g., from no phones to cell phones - bypassing landlines all together. However, leapfrogging from unreliable infrastructure systems to 'smart' cities is too large a jump resulting in unsustainable and unhealthy infrastructure systems. In the Global South, a baseline of unreliable infrastructure is a prevalent problem. The push for sustainable and 'smart' [re]development tends to ignore many of those already living with failing, unreliable infrastructure. Without awareness of baseline conditions, uninformed projects run the risk of returning conditions to the status quo, keeping many urban populations below targets of the United Nations' Sustainable Development Goals. A key part of understanding the baseline is to identify how citizens have long learned to adjust their expectations of basic services. To compensate for poor infrastructure, most residents in the Global South invest in remedial secondary infrastructure (RSI) at the household and business levels. The authors explore three key 'smart' city transformations that address RSI within a hierarchical planning pyramid known as the comprehensive resilient and reliable infrastructure systems (CRISP) planning framework.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Milestones for Selection, Characterization, and Analysis of the Performance of a Repository for Spent Nuclear Fuel and High-Level Radioactive Waste at Yucca Mountain.

This report presents a concise history in tabular form of events leading up to site identification in 1978, site selection in 1987, subsequent characterization, and ongoing analysis through 2009 of the performance of a repository for spent nuclear fuel and high - level radioactive waste at Yucca Mountain in southern Nevada. The tabulated events generally occurred in five periods: (1) commitment to mined geologic disposal and identification of sites; (2) site selection and analysis, based on regional geologic characterization through literature and analogous data; (3) feasibility analysis demonstrating calculation procedures and importance of system components, based on rough measures of performance using surface exploration, waste process knowledge, and general laboratory experiments; (4) suitability analysis demonstrating viability of disposal system, based on environment - specific laboratory experiments, in - situ experiments, and underground disposal system characterization; and (5) compliance analysis, based on completed site - specific characterization . The current sixth period beyond 2010 represents a new effort to set waste management policy in the United States. Because the relationship is important to understanding the evolution of the Yucca Mountain Project , the tabulation also shows the interaction between the policy realm and technical realm using four broad categories of events : (a) Regulatory requirements and related federal policy in laws and court decisions, (c) Presidential and agency directives, (c) technical milestones of implementing institutions, and (d) critiques of the Yucca Mountain Project and pertinent national and world events related to nuclear energy and radioactive waste. Preface The historical progression of technical milestones for the Yucca Mountain Project was originally developed for 10 journal articles in a special issue of Reliability Engineering System Safety on the performance assessment for the Yucca Mountain license application [1-10]. The listing of mile stones, a distinct feature of those articles, has been collected and tabulated here. A lthough a brief description is presented here (based on the summaries in the 10 journal articles), the emphasis remains on the tabulation because of its usefulness in providing a comprehensive but concise history of the Yucca Mountain Project. The tabulation presented here is more elaborate than originally presented in that many of the interactions that occurred between the technical realm and policy realm can be depicted in separate columns. The usefulness of the milestones table is due in part to L.A. Connolly, for editorial and reference support, and S.K. Best, Raytheon, and L. Mays, Sandia National Laboratories (SNL), for illustration support. Reviewers P.N. Swift, SNL, and K. Gupta, University of Oklahoma, helped improve the discussion. The historical perspective presented is that of the author and is not necessarily held by reviewers, Sandia National Laboratories , and the US Department of Energy. As a historic perspective, the author is reporting on the work of others; however, any interpretative error s of the documentation are those of the author alone. The characterization and modeling of the Yucca Mountain disposal system required numerous participants with expertise in many areas of science and technology, as evident from the extensive reference list. Their diligent efforts are generally acknowledged here and through the many references to their impressive work, but the 10 journal articles acknowledge by name many of the numerous participants that contributed to the Yucca Mountain Project .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Coastal Acoustic Buoy for Offshore Wind: Project Synthesis

The population of North Atlantic right whales is critically endangered and their habitat overlaps with offshore windfarm leases. It is therefore imperative that effective mitigation strategies be used to avoid impacts on right whales during the construction of offshore windfarms. The Department of Energy issued FOA Number DE-FOA-0001924 to encourage the development of technology that could monitor large exclusion zones for right whales in order to mitigate potential impact of construction noise on right whales. This report summarizes the past two years of the development and evaluation of the Coastal Acoustic Buoy for Offshore Wind (CABOW) project which aimed to develop technology to monitor large exclusion zones for North Atlantic right whales. Over the course of the project SMRU Consulting have implemented a rigorous design process including comparison of different approaches (e.g., single sensor vs multiple sensors), as well as consideration of placement and timing of acoustic monitoring. We have evaluated critical components of the CABOW system including, reliability, detection range, and bearing accuracy in areas adjacent to offshore windfarm leases in Maryland by conducting 3,536 playbacks of simulated right whale upcalls. The maximum call detection range was 7.5 km when noise was 99 dB re 1µPa rms (50-225 Hz), but this reduced to < 1 km when ambient noise levels were high. Our detection probability in the field was measured as a function of range as well as the source-to-noise level ratio allowing us to build a model to predict the probability of detection under various scenarios (sample size: 3,536 calls x 5 buoys = 17,680). The median bearing error was -0.25° but this is likely an underestimate of error due to experimental design. Using the published recall and precision of the two detectors we implemented in the CABOW system, we estimate that at a recall of 80%, our precision was > 80%, within the range of what we were aiming for in this project. To estimate our exclusion zone false negative and false positive rates, we built a simulation model using the empirical data from our field trial. We modelled three to nine CABOW units placed on the 10 km exclusion zone and estimated our false negative rate to be 1% or less (which was our project goal) and our false positive rate to be between seven and nine percent, slightly above our goal of 5%. However, we also modelled an equivalent PAM system that does not have bearing capabilities and found the false positive rates for that system to be six to eight times higher than the CABOW rate. This higher false positive rate of PAM systems with low spatial information could have significant cost repercussions for offshore wind developers by adding work shutdowns or delays without providing additional protection for right whales. The model we built allows us to explore the placement of PAM systems under various scenarios and will thus help facilitate planning of PAM mitigation systems to meet NOAA Incidental Harassment Authorizations for specific windfarms. We achieved an average system uptime of 98.3%, just below our goal of 99%. The issues that caused these short losses of data have been identified and fixed. Right whale detections and audio clips were typically transferred via radio from the buoys to the base station in two to four seconds. We therefore believe we have developed a highly robust real-time PAM system. Based on the above, we feel we have achieved the stated funding goal of developing a cost-effective and robust real-time PAM system that enables the monitoring of large exclusion zones for right whales during the constructions of offshore windfarms. This should lead to decreased costs and risks for the offshore wind sector while providing robust mitigation for right whales. It is important to state that PAM mitigation will need to be implemented with other mitigation strategies (e.g., visual observers) to provide a complete mitigation strategy to ensure that any effects on right whales from offshore windfarm construction is minimized.

17 WIND ENERGY↗

Evaluation Of Year 2020 IEEE RTS Generation Reliability Indices

A new IEEE Reliability Test System (2017 update) with wind and solar sources modeling 2020 has been created by NREL and posted on the GitHub RTS-GMLC repository. A simple procedure duplicates the 1979 RTS 'exact' indices and calculates indices for the 1996 RTS and the new 2020 Model RTS 'exact' indices. Extremely fast execution is realized by simply 'looking up' the exact LOLPs each hour from a COPT. Wind and solar are treated as hourly demand reducers. Computer program codes are included.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Bayesian and HRA-Aided Method for the Novel Reliability Analysis of Software

Technological advancements and nuclear power plant modernization has inspired considerable research in the areas of safety and reliability, yet there remains a lack of consensus for the reliability assessment of digital instrumentation and control (I&C) systems. Motivated by the lack of consensus for reliability analysis methods, this work employs a novel framework that incorporates Bayesian, human reliability, and common-cause failure (CCF) modeling techniques. The novel framework allows the use of state-of-the-art or classical modeling techniques when accounting for human and CCF effects on system reliability. The Bayesian and HRA-Aided Method for the Reliability Analysis of Software (BAHAMAS) is demonstrated by a case study for the quantification of software hazards found in a previous analysis of a digital reactor trip system. The results demonstrate the ability of BAHAMAS to account for human activities during the software development life cycle and their influence on software reliability. BAHAMAS is a flexible tool for extending the coverage of conventional probabilistic risk assessments to include modernized digital I&C systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Outage Analysis for Cooperative mmWave UAV Communications With Beam Training Overhead

In this letter, we investigate the tradeoff between reliability and beam training overhead in cooperative millimeter wave (mmWave) unmanned aerial vehicle (UAV) communications. In particular, we analyze how outage probability varies with the number of neighboring UAVs being probed as potential relays for relay selection. Unlike existing work, the limited number of UAV beams as well as UAV orientations are explicitly considered in our analysis. Here we derive the outage probability in closed form and verify our analysis via simulations. The results facilitate us to understand the fundamental limits of cooperative mmWave UAV communications.

99 GENERAL AND MISCELLANEOUS↗

Module Degradation Mechanisms Studied by a Multi-Scale Approach

A key pathway to meeting the Department of Energy SunShot 2020 goals is to reduce financing costs by improving investor confidence through improved photovoltaic (PV) module reliability. A comprehensive approach to further understand and improve PV reliability includes characterization techniques and modeling from module to atomic scale. Imaging techniques, which include photoluminescence, electroluminescence, and lock-in thermography, are used to locate localized defects responsible for module degradation. Small area samples containing such defects are prepared using coring techniques and are then suitable and available for microscopic study and specific defect modeling and analysis.

14 SOLAR ENERGY↗