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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 379 records · Page 21

Joint Design of Multimodal Transit Networks and Shared Autonomous Mobility Fleets

Providing quality transit service to travelers in low-density areas, particularly travelers without personal vehicles, is a constant challenge for transit agencies. The advent of fully-autonomous vehicles (AVs) and their inclusion in mobility service fleets may allow transit agencies to offer better service and/or reduce their own capital and operational costs. This study focuses on the problem of allocating resources between transit patterns and operating (or subsidizing) shared-use AV mobility services (SAMSs) in a large metropolitan area. To address this question, a joint transit network redesign and SAMS fleet size determination problem (JTNR-SFSDP) is introduced, and a bi-level mathematical programming formulation and solution approach are presented. The upper-level problem modifies a transit network frequency setting problem (TNFSP) formulation via incorporating SAMS fleet size as a decision variable and allowing the removal of bus routes. The lower-level problem consists of a dynamic combined mode choice-traveler assignment problem (DCMC-TAP) formulation. The heuristic solution procedure involves solving the upper-level problem using a nonlinear programming solver and solving the lower-level problem using an iterative agent-based assignment-simulation approach. To illustrate the effectiveness of the modeling framework, this study uses traveler demand from Chicago along with the regions existing multimodal transit network. The computational results indicate significant traveler benefits, in terms of improved average traveler wait times, associated with optimizing the joint design of multimodal transit networks and SAMS fleets compared with the initial transit network design.

bi-level programming↗

LevSeq: Rapid Generation of Sequence-Function Data for Directed Evolution and Machine Learning

Sequence-function data provides valuable information about the protein functional landscape but is rarely obtained during directed evolution campaigns. Here, we present Long-read every variant Sequencing (LevSeq), a pipeline that combines a dual barcoding strategy with nanopore sequencing to rapidly generate sequence-function data for entire protein-coding genes. LevSeq integrates into existing protein engineering workflows and comes with open-source software for data analysis and visualization. The pipeline facilitates data-driven protein engineering by consolidating sequence-function data to inform directed evolution and provide the requisite data for machine learning-guided protein engineering (MLPE). LevSeq enables quality control of mutagenesis libraries prior to screening, which reduces time and resource costs. Simulation studies demonstrate LevSeq’s ability to accurately detect variants under various experimental conditions. Lastly, we show LevSeq’s utility in engineering protoglobins for new-to-nature chemistry. Widespread adoption of LevSeq and sharing of the data will enhance our understanding of protein sequence-function landscapes and empower data-driven directed evolution.

59 BASIC BIOLOGICAL SCIENCES↗

Resolving Away Stratocumulus Biases in Modern Global Climate Models

Abstract Increased horizontal and vertical resolution in global atmospheric models can reduce a significant amount of the biases associated with subtropical marine stratocumulus. The sensitivity of offshore and coastal marine stratocumulus to different horizontal and vertical resolutions has been investigated by using Energy Exascale Earth System Model (E3SM) coupled with the novel Framework for Improvement by Vertical Enhancement which has been demonstrated as a viable tool to improve the representation of marine stratocumulus while saving computational cost. Our study shows that high vertical resolution is the key to improve marine stratocumulus simulations in E3SM. Concurrent horizontal and vertical resolution increases are needed for substantial overall reduction of stubborn marine stratocumulus biases over the coastal region but not necessarily in the offshore area.

54 ENVIRONMENTAL SCIENCES↗

Correlating AGP on a quantum computer

For variational algorithms on the near term quantum computing hardware, it is highly desirable to use very accurate ansatze with low implementation cost. Recent studies have shown that the antisymmetrized geminal power (AGP) wavefunction can be an excellent starting point for ansatze describing systems with strong pairing correlations, as those occurring in superconductors. In this work, we show how AGP can be efficiently implemented on a quantum computer with circuit depth, number of CNOTs, and number of measurements being linear in system size. Using AGP as the initial reference, we propose and implement a unitary correlator on AGP and benchmark it on the ground state of the pairing Hamiltonian. Furthermore, the results show highly accurate ground state energies in all correlation regimes of this model Hamiltonian.

97 MATHEMATICS AND COMPUTING↗

Dynamical structure factors of warm dense matter from time-dependent orbital-free and mixed-stochastic-deterministic density functional theory

Abstract We present the first calculations of the inelastic part of the dynamical structure factor (DSF) for warm dense matter (WDM) using time-dependent orbital-free density functional theory (TD-OF-DFT) and mixed-stochastic-deterministic (mixed) Kohn Sham TD-DFT (KS TD-DFT). WDM is an intermediate phase of matter found in planetary cores and laser-driven experiments, where the accurate calculation of the DSF is critical for interpreting x-ray Thomson scattering measurements. Traditional TD-DFT methods, while highly accurate, are computationally expensive, motivating the exploration of TD-OF-DFT and mixed TD-KS-DFT as more efficient alternatives. We applied these methods to experimentally measured WDM systems, including solid-density aluminum and beryllium, compressed beryllium, and carbon–hydrogen mixtures. Our results show that TD-OF-DFT requires a dynamical kinetic energy potential in order to qualitatively capture the plasmon response. Additionally, it struggles with capturing bound electron contributions. In contrast, mixed TD-KS-DFT offers greater accuracy in distinguishing bound and free electron effects, aligning well with experimental data, though at a higher computational cost. This study highlights the trade-offs between computational efficiency and accuracy, demonstrating that TD-OF-DFT remains a valuable tool for rapid scans of parameter space, while mixed TD-KS-DFT should be preferred for high-fidelity simulations. Our findings provide insight into the future development of DFT methods for WDM and suggest potential improvements for TD-OF-DFT.

36 MATERIALS SCIENCE↗

Destructive Error Interference in Product-Formula Lattice Simulation

Quantum computers can efficiently simulate the dynamics of quantum systems. Here, we study the cost of digitally simulating the dynamics of several physically relevant systems using the first-order product-formula algorithm. We show that the errors from different Trotterization steps in the algorithm can interfere destructively, yielding a much smaller error than previously estimated. In particular, we prove that the total error in simulating a nearest-neighbor interacting system of n sites for time t using the first-order product formula with r time slices is O ( n t / r + n t 3 / r 2 ) when n t 2 / r is less than a small constant. Given an error tolerance ϵ , the error bound yields an estimate of max { O ( n 2 t / ϵ ) , O ( n 2 t 3 / 2 / ϵ 1 / 2 ) } for the total gate count of the simulation. The estimate is tighter than previous bounds and matches the empirical performance observed in Childs et al. [ Proc. Natl. Acad. Sci. U.S.A. 115 , 9456 (2018) ]. We also provide numerical evidence for potential improvements and conjecture an even tighter estimate for the gate count.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Shadow Distillation: Quantum Error Mitigation with Classical Shadows for Near-Term Quantum Processors

Mitigating errors in quantum information processing devices is especially important in the absence of fault tolerance. An effective method in suppressing state-preparation errors is using multiple copies to distill the ideal component from a noisy quantum state. Here, we use classical shadows and randomized measurements to circumvent the need for coherent access to multiple copies at an exponential cost. We study the scaling of resources using numerical simulations and find that the overhead is still favorable compared to full state tomography. We optimize measurement resources under realistic experimental constraints and apply our method to an experiment preparing a Greenberger-Horne-Zeilinger state with trapped ions. In addition to improving stabilizer measurements, the analysis of the improved results reveals the nature of errors affecting the experiment. Hence, our results provide a directly applicable method for mitigating errors in near-term quantum computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Understanding relative metal prices and availability: Combining physical and economic perspectives

Abstract Scientists typically use physical indicators, such as average crustal abundance, and energy requirements in production, as measures of the availability of mineral resources. Economists, on the other hand, typically rely on measures such as prices, and extraction costs. This study investigates the role of crustal abundance, energy requirements, and other physical indicators in determining relative metal prices. The relationship between prices, and physical indicators is estimated statistically for a sample of 22 chemical elements over the period 1970–2013 using an economic market model. The results suggest that energy requirements in production explain 43% of observed variation in metal prices, crustal abundance 21%, and other physical indicators (toxicity, native metal status, and melting point) combine to explain 12% of the observed differences in metal prices.

Watson, Brett J.↗

Recyclable Cellulose Fiber Reinforced Vitrimer Composite

Vitrimer is an innovative class of polymeric materials which demonstrates traditional thermoset-like mechanical and chemical resilience while still being able to flow on demand like a traditional thermoplastic through covalently adaptive dynamic linkages. Herein, high-performance cellulose fiber reinforced vitrimer composites are developed using an epoxy-based vitrimer and natural cellulose paper. The reinforced vitrimer composite was fabricated by impregnating the porous structure of cellulose paper with two curable monomers, followed by in-situ polymerization of the monomers inside the fibrous scaffold. The introduction of hydroxyl group present on the cellulosic framework assisted in a faster topological rearrangement of the crosslinked matrix through transesterification exchange reaction, thus imparting various sought-after properties like shape recovery and recyclability via simple thermal reprocessing. Moreover, the reinforced vitrimer composite exhibits superior tensile properties as high as 90 MPa with 15-25 volume% vitrimer loading due to the interfacial adhesion via ester exchange reaction between the epoxy matrix and functionalities on the cellulosic fibers. Noteworthily, the key ingredients of the resulting composite (i.e., epoxy-based vitrimer and cellulose fibers) can be comfortably recycled without using aggressive chemical treatment, enabling composite to be easily recycled or disposed of at the end of service life and assist in reducing the subsequent manufacturing cost. This study would shed light on the development of a recyclable polymer composite with exceptional mechanical properties while simultaneously demonstrating self-healing and shape memory capabilities.

Rohewal, Sargun Singh↗

Performance trade-offs in reconfigurable networks for HPC

Designing efficient interconnects to support high-bandwidth and low-latency communication is critical toward realizing high performance computing (HPC) and data center (DC) systems in the exascale era. At extreme computing scales, providing the requisite bandwidth through overprovisioning becomes impractical. These challenges have motivated studies exploring reconfigurable network architectures that can adapt to traffic patterns at runtime using optical circuit switching. Despite the plethora of proposed architectures, surprisingly little is known about the relative performances and trade-offs among different reconfigurable network designs. We aim to bridge this gap by tackling two key issues in reconfigurable network design. First, we study how cost, power consumption, network performance, and scalability vary based on optical circuit switch (OCS) placement in the physical topology. Specifically, we consider two classes of reconfigurable architectures: one that places OCSs between top-of-rack (ToR) switches—ToR-reconfigurable networks (TRNs)—and one that places OCSs between pods of racks—pod-reconfigurable networks (PRNs). Second, we tackle the effects of reconfiguration frequency on network performance. Our results, based on network simulations driven by real HPC and DC workloads, show that while TRNs are optimized for low fan-out communication patterns, they are less suited for carrying high fan-out workloads. PRNs exhibit better overall trade-off, capable of performing comparably to a fully non-blocking fat tree for low fan-out workloads, and significantly outperform TRNs for high fan-out communication patterns.

Teh, Min Yee↗

Selection of representative general circulation models under climatic uncertainty for Western North America

Abstract Climate change research uses an ensemble of general circulation model runs (GCMs-runs) to predict future climate under uncertainties. To reduce computational costs, this study selects representative GCM-runs (RGCM-runs) for Western North America (WNA) based on their performance in replicating historical climate conditions from 1981 to 2005 and projecting future changes from 1981–2010 to 2071–2100. This evaluation is conducted under two representative concentration pathways (RCPs) scenarios, RCP4.5 and RCP8.5, from the Coupled Model Intercomparison Project 5. By using an envelope-based selection technique and a multi-objective distance-based approach, we identify four RGCM-runs per RCP representing diverse climatic conditions, including wet-warm, wet-cold, dry-warm, and dry-cold. Compared to the full-set, these selected runs show a decreased mean absolute error (MAE) between the reference and RGCM-runs concerning the monthly average mean air temperature (T̄) and precipitation (P̄). For RCP4.5, T̄ MAE is 0.45 (vs. 0.58 in the full-set) and P̄ MAE is 0.31 (vs. 0.42). For RCP8.5, T̄ MAE is 0.51 (vs. 0.75) and P̄ MAE is 0.25 (vs. 0.36). The lower MAE values in the RGCM-run set indicate closer alignment between predicted and reference values, making the RGCM-run suitable for climate impact assessments in the region.

Water Resources↗

Using Geophysical Technologies Deployed in Inexpensive Monitoring Wells to Monitor the Evolution of a CO 2 Plume: Potential Benefits and R&D Needs

This report demonstrates the potential benefits of an R&D program designed to substantially decrease the cost of drilling monitoring wells. The study determines the costs of monitoring a commercial-scale CO 2 storage project's CO 2 plume using a vertical seismic profile (VSP) array. The VSP array consists of permanent surface orbital vibrator (SOV) seismic sources and distributed acoustic sensing (DAS) fiber optic cable receivers permanently installed in shallow monitoring wells. Several scenarios are assessed varying the costs of drilling monitoring wells for DAS to evaluate the potential benefits of an R&D program to lower well costs. The monitoring costs of VSP are compared against those of 4-D seismic surveys which deploy temporary seismic sources and receivers. If the cost of monitoring wells can be lowered about 50%, VSP monitoring is a more attractive cost option than 4-D seismic for CO 2 plume monitoring, warranting future R&D efforts to lower these costs.

58 GEOSCIENCES↗

Proceedings from the State of the Science and Technology for Minimizing Impacts to Bats from Wind Energy

The U.S. Department of Energy Wind Energy Technologies Office (DOE WETO), and the National Renewable Energy Laboratory convened a workshop entitled the State of the Science and Technology for Minimizing Impacts to Bats from Wind Energy on 13–14 November 2019. The objectives of the workshop were to (1) Identify the current impact minimization measures that are, or can be, used to reduce bat fatalities at wind energy facilities, (2) Assess the current effectiveness of those minimization measures, (3) Identify and assess the research and development (R&D) opportunities needed to optimize and improve the effectiveness of current minimization and deterrent technologies and inform the development of future solutions; and (4) Identify potential emerging or novel methods for informing impact minimization measures at or around wind energy facilities. Specifically, the workshop focused on deterrent and curtailment strategies. For deterrents, the discussion centered on the existing technology (i.e., ultrasonic deterrents, dim-UV light, and texture coating), integration with wind turbines (either retrofitting or out of the box installation), effectiveness, validation studies, and cost (e.g., technology, installation, validation, and maintenance). For curtailment, the conversation was divided into blanket curtailment (i.e., based on time and wind speed) and smart curtailment (i.e., blanket curtailment plus additional variables such as temperature or bat activity). The workshop included plenary presentations, panels, and breakout sessions to share data and stakeholder perspectives, and engage participants. Although there are several priority topics related to bat and wind energy, this workshop focused the discussion on the current technologies and strategies that are, or can be, used to reduce bat fatalities at wind energy facilities, status of research and development (R&D) of minimization measures, opportunities to optimize costs and improve effectiveness, and potential emerging or novel approaches to explore. This workshop took a holistic approach and discussed all aspects associated with advancing deterrent technologies and curtailment strategies, including the technological, biological, economic, and regulatory barriers faced by the wind energy and wildlife community.

13 HYDRO ENERGY↗

Characterizing Heat Transfer in sCO 2 Cycle Coolers Utilizing the Wilson Plot Technique

Effective design of coolers can decrease the capital expense of supercritical carbon dioxide (sCO 2 ) power plants. Improved datasets reporting heat transfer from the CO 2 in the cycle cooler allow design engineers to calculate the required length of heat exchanger streams more accurately, thus reducing cooler material and heat exchanger cost. This study considered a shell-and-tube heat exchanger with non-condensing CO 2 on the tube side and water flow on the shell side. The average Nusselt number on the tube side was measured employing the Wilson plot technique for a flow at a Reynolds number, Re, equal to 1×10 5 and for a heat flux to mass flux ratio, Q"/G, ranging from 50 to 350 J/kg. The results indicate that the Nusselt number, Nu, increases as the CO 2 pressure decreases towards the critical point. The results also indicate that Nu increases to maximum at Q"/G = 215 J/kg and then decreases with further increases in Q"/G. The difference in Nu measured between the horizontal and vertical heat exchanger with downward flowing CO 2 is less than the experimental error.

20 FOSSIL-FUELED POWER PLANTS↗

Simplified High-Temperature Molten Salt CSP Plant Preconceptual Design

State of the art concentrating solar power plants generally rely on a two-tank system with a large central tower. These plants employ nitrate salts that are limited to approximately 565°C in practice. A novel system arrangement is proposed using molten salt as the heat transfer and energy storage media in a single thermocline storage tank with an integral heat exchanger to the power cycle. The system has unique features that enable temperatures higher than 565°C while reducing costs. This study explores the considerations for the concept and presents a preconceptual point design for a 5 MWt system capable of generating 100 MWt per day with 12 hours of thermal energy storage. This study also examines the potential operation of the system with nitrate and higher temperature chloride salts. Both salt systems appear promising and future concept maturation is recommended.

14 SOLAR ENERGY↗

A Detailed Vehicle Modeling & Simulation Study Quantifying Energy Consumption and Cost Reduction of Advanced Vehicle Technologies Through 2050

The U.S. Department of Energy (DOE) Vehicle Technologies Office (VTO) and Hydrogen and Fuel Cell Technologies Office (HFTO) aim to develop sustainable, affordable, and efficient technologies for transportation of goods and people. Translating investments in advanced transportation component technologies and powertrains to estimate vehicle-level fuel savings potential is critical for understanding DOE’s impact. In this work, we simulated technologies funded by VTO and HFTO for light duty vehicles. The simulations were performed across: (1) Multiple powertrain configurations (conventional, power-split, extended-range electric vehicle, battery electric drive, and fuel-cell vehicles); (2) Vehicle classes (compact car, midsize car, small sport utility vehicle [SUV], midsize SUV, and pickup trucks); and (3) Fuels (gasoline, diesel, natural gas, hydrogen, and battery electricity). These various technologies are assessed for six different timeframes: laboratory years 2015 (reference), 2020, 2025, 2030, and 2045. A delay of five years is assumed between laboratory year and model year (the year the technology is introduced into production).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Next Generation Durable, Cost Effective, Energy Efficient Tubular SOFC (Final Scientific/Technical Report)

The overall objective of this project is to develop and optimize a YSZ electrolyte-based solid oxide fuel cell (SOFC) technology for low cost, low temperature (~ 650°C), and high energy efficiency operation. The developed technology will be implemented and demonstrated in a high efficiency 2~3kW SOFC with applicability to sub-MW systems. A summary of significant accomplishments is provided below. Key accomplishments: 1. Improved fundamental cell technology demonstrated at single tube and system scale. Improved power output by 54% while operating at the normal temperature of 750°C. And improved power output by 33% while operating at 650°C, 100°C lower than normal temperature. 2. SPS patented internal recycle arrangement was developed and extended to operate on LPG fuel directly in a compact, high-efficiency (> 40%) system. 3. System testing was conducted to prove the long-term durability of cell improvements. Demonstrated over 8000 hours of operation at 0.21 %/1000 hrs degradation. 4. A large-scale, 2.5kW net power system demonstration was completed, which demonstrated 40% net efficiency over 1000 hours. 5. System design and cost analysis of a 1MW system utilizing a 2.5kW bundle was completed. Cost optimization of the bundle showed a reduction of nearly 80% is possible from $\$$5,790/kW to $\$$1250/kW. This lower cost is considered viable for SPS commercialization.

03 NATURAL GAS↗

Comparative Analysis of DNA LLM Classification Techniques Using Intra-Layer Feature Extraction with Autoencoder Stacks [Poster]

This project conducts a comparative analysis of DNA LLM classification techniques using Evo2, Grover, and UTRML, focusing on intra-layer feature extraction in Evo2. By extracting features from multiple layers of Evo2 and integrating them into an autoencoder stack with a binary classification head, we evaluate its effectiveness in classifying genomic sequences compared to smaller DNA language models. My findings demonstrate that Evo2 outperforms Grover and UTRML in classification accuracy on a dataset provided by department 08625, CAO2021, while UTRML offers competitive performance with lower computational costs. This study highlights the potential of advanced embedding techniques in enhancing genomic data analysis and informs future research in bioinformatics.

59 BASIC BIOLOGICAL SCIENCES↗