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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Probabilistic Programming for Transportable Source Characterization and Uncertainty Quantification of the North Korean Nuclear Tests 2006–2017

Here, we introduce a transportable technique to determine the yield and depth of burial (DOB) from seismic source spectra of underground nuclear explosions. We demonstrate this technique on the six declared North Korean nuclear tests. This approach derives source spectra in absolute units from regional phase (Pg) amplitudes by correcting the observations for geometric spreading, attenuation, and site amplification. We couple the source spectra and explosion source models with a probabilistic programming framework that integrates deep learning techniques and Bayesian modeling. This approach permits the exchange of information across various data categories to quantify both the data and model uncertainty. This technique stands out as an innovative use of broad‐area propagation models, making it transportable across various geologic settings. This method proves to be effective in scenarios with diverse and/or limited observational data, even when the source depth is unknown. We present new independent estimates of absolute yield and DOB that are consistent with the prior assessments, underscoring the potential of this method in enhancing transportable nuclear explosion monitoring capabilities.

58 GEOSCIENCES↗
DOE OSTI2022

Assessing the Interactive Impacts of Energy Efficiency and Demand Response on Power System Costs and Emissions

Utilities are increasingly interested in integrating energy efficiency (EE) and demand response (DR) measures and technologies (as well as other distributed energy resources) as a strategic approach to improve their cost-effectiveness and performance. However, the specific EE and DR features that may be best integrated, the interplay between changing EE and DR resource potential, and resulting utility system impacts are not well understood. We quantify the impacts of EE and DR in isolation and in combination on bulk power system costs and emissions based on changes in generation expansion, transmission expansion, and dispatch patterns. The study methodology mimics utility resource planning and uses more novel techniques to select least-cost generation and transmission capacity from supply-and demand-side resources, as compared to more commonly used utility approaches that only consider supply-side resources. The results identify key EE and DR characteristics affecting each other’s power system value and the most valuable technologies and strategies that can be jointly deployed. We discuss implications for EE and DR cost-effectiveness frameworks, program design, and integrated resource planning.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Applying Quantum Computing to Simulate Power System Dynamics

Power system dynamics are generally modeled by high dimensional nonlinear differential-algebraic equations due to a large number of generators, loads, and transmission lines. Thus, its computational complexity grows exponentially with the system size. This paper demonstrates the potential use of quantum computing algorithms to model the power system dynamics. Leveraging a symbolic programming framework, we equivalently convert the power system dynamics’ differential algebraic equations (DAEs) into ordinary differential equations (ODEs), where the data of the state vector can be encoded into quantum computers via amplitude encoding. The system's nonlinearity is captured by Taylor polynomial expansion, the quantum state tensor, and Hamiltonian simulation, whereas state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can simulate the dynamics of the power system with high accuracy, whereas its complexity is polynomial in the logarithm of the system dimension. Our work also illustrates the use of scientific machine learning tools for implementing scientific computing concepts, e.g., Taylor expansion, DAEs/ODEs transform, and quantum computing solver, in the field of power engineering.

Tran, Huynh↗
DOE OSTI2026

Optimizing district energy systems by integrating Borehole Thermal Energy Storage Using a Mixed-Integer Linear Programming g-function framework with a Multi-Timescale Rolling Horizon method

Shallow geothermal has gained increasing attention in recent years; however, a reliable framework for its accurate incorporation into large-scale energy system optimization remains lacking. This study proposes a Mixed-Integer Linear Programming (MILP) framework combined with the g-function approach to integrate Borehole Thermal Energy Storage (BTES) technology into energy system optimization. Validation against a Modelica-based reservoir network simulation demonstrates that the proposed framework effectively captures the ground thermal response under varying energy loads and accurately estimates the borefield energy supply. To enhance scalability, a Rolling Horizon with Multi-Timescale (RH-MTS) method is further introduced, reducing computational time by 73 % for the 1-year optimization model with only minor loss of optimality. The framework is demonstrated through the case study of the UC Berkeley campus. Results indicate that BTES is a cost-effective and low-carbon solution: two borefields comprising 382 boreholes can meet 8.0 % and 6.6 % of the total campus heating and cooling demand, respectively, at an average energy rate of 0.70–0.77 USD/kWh and carbon intensity of 0.54 kg-CO2/kWh. Short-term analysis reveals a 35%–65% decline in BTES energy flow after 3–6 months of continuous heating/cooling operation, while long-term simulation shows that annual energy production of BTES can vary by up to 12.0 % after four years before stabilizing. Overall, this study develops a novel optimization framework that couples physics-based g-function method with MILP optimization framework, thereby advancing methodological development for shallow-geothermal integration and providing actionable guidance for BTES deployment in district-energy systems.

Yang, Jiahui↗
DOE OSTI2024

Building a Clean Energy Workforce: An Evaluation Framework for State Energy Office Workforce Programs

This fact sheet is a summary of the workforce evaluation framework that was first proposed in the white paper, An Evaluation Framework for State Energy Offices' Energy Efficiency and Clean Energy Workforce Program. This evaluation framework was developed to guide State Energy Offices (SEOs) in assessing and enhancing the workforce development programs the manage, fund, or partner on. By following this step-by-step framework, SEOs can evaluate program components, identify areas for improvement, and optimize program outcomes for greater impact.

clean energy↗
DOE OSTI2023

A Pulse Generation Framework with Augmented Program-aware Basis Gates and Criticality Analysis

Near-term intermediate scale quantum (NISQ) de- vices are subject to considerable noise and short coherence time. Consequently, it is critical to minimize circuit execution latency. Traditionally, each basis gate of a transpiled circuit is decoded into a fixed episode of the device control pulses. Recently, people started to investigate merged pulse generation for customized gates through quantum optimal control (QOC). However, existing QOC approaches face the challenges of (i) restricted search space due to prohibitive compilation overhead; (ii) suboptimal end-to-end performance due to aggressive local optimization and falsely introduced dependency among the customized gates; (iii) inadequate adaptivity towards system calibration, which is critical for NISQ devices. In this work, we propose PAQOC, a novel QOC framework that can (i) automatically detect frequently encountered gate patterns in the logical circuit by modeling the problem as a subgraph mining process and reuse these patterns to enable much larger search space exploration (i.e., program aware); (ii) systemically construct customized gate-set based on the impact to the overall program latency (i.e., criticality-aware); and (iii) quickly adapt to system re-calibration thanks to the small-scale pattern-based gate generation (i.e., adaptivity-aware). PAQOC achieves a good tradeoff between circuit performance and compilation time, allowing fully automatic, single stop, ad- hoc customized pulse generation for more efficient execution of user programs on NISQ devices. Evaluations using fifteen applications show that PAQOC can achieve on average 1.95× speedup of the circuit latency and achieve on average 36.7% reduction in compilation overhead. With PAQOC, circuits can run faster with reduced noise, allowing deeper circuits to be tested within the coherence time of present NISQ platforms.

Chen, Yanhao↗
DOE OSTI2023

Statistical Framework for Planning a Shelf Life Program with Binary Performance Data

This document outlines a statistical framework for establishing a shelf-life program for components whose performance is measured by a binary response, usually ‘pass’ or ‘fail.’ The approach applies to both single measurement devices and repeated measurement devices. The high-level objective of these plans is to quickly detect any sizeable increase in fraction defective as the product ages. The statistical approach is to choose a sample size and monitoring technique that alarms when the fraction defective increases to an unacceptably high level, but does not alarm when the process is at nominal. The nominal (acceptable) fraction defective is used, and an increased fraction defective (unacceptable) is assumed as part of the control chart design. The control chart recommended for this problem is the Bernoulli Cumulative Sum (CUSUM) control chart.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

High-Level Synthesis of Parallel Specifications Coupling Static and Dynamic Controllers

The increased need for efficient ways to implement domain-specific accelerators is driving design methodologies towards the use of abstractions higher than the Register Transfer Level (RTL). In this scenario, High Level Synthesis (HLS) plays a significant role by enabling the automatic generation of custom hardware accelerators starting from high level descriptions (e.g., C code). Conventional HLS tools exploit parallelism mostly at the Instruction Level (ILP). They statically schedule the input specifications, and build centralized Finite State Machine (FSM) controllers. However, aggressive exploitation of ILP in many applications has diminishing returns and, usually, centralized approaches do not efficiently exploit coarser parallelism because FSMs are inherently serial. In this paper we present a HLS framework able to synthesize applications that, beside ILP, also expose Task Level Parallelism (TLP). An application can expose TLP through annotations that identify the parallel functions (i.e., tasks). To generate accelerators that efficiently execute concur- rent tasks, we need to solve several issues: devise a mechanism to support concurrent execution flows, exploit memory parallelism, and manage synchronization. To support concurrent execution flows, we introduce a novel adaptive controller. The adaptive controller is composed of a set of interacting control elements that independently manage the execution of a single operation or function call. These control elements check dependencies and resource constraints at runtime, enabling as soon as possible execution. To support parallel access to shared memories and synchronization, we introduce a novel Hierarchical Memory Interface (HMI). With respect to previous solutions, the proposed interface supports multi-ported memories and atomic memory operations, which commonly occur in parallel programming. Our framework can generate the hardware implementation of C functions by employing two different approaches, depending on its characteristics. If a function exposes TLP, then the framework generates hardware implementations based on the adaptive controller. Otherwise, the framework implements the function by exploiting a more conventional FSM approach, which is optimized for ILP exploitation. We evaluate our framework on a set of parallel applications, and show substantial performance improvements (average speedup of 4.7) with limited area over- heads (average area increase of 5.48 times).

Castellana, Vito G.↗
DOE OSTI2021

High-Level Synthesis of Parallel Specifications Coupling Static and Dynamic Controllers

The increased need for efficient ways to implement domain-specific accelerators is driving design methodologies towards the use of abstractions higher than the Register Transfer Level (RTL). In this scenario, High Level Synthesis (HLS) plays a significant role by enabling the automatic generation of custom hardware accelerators starting from high level descriptions (e.g., C code). Conventional HLS tools exploit parallelism mostly at the Instruction Level (ILP). They statically schedule the input specifications, and build centralized Finite State Machine (FSM) controllers. However, aggressive exploitation of ILP in many applications has diminishing returns and, usually, centralized approaches do not efficiently exploit coarser parallelism because FSMs are inherently serial. In this paper we present a HLS framework able to synthesize applications that, beside ILP, also expose Task Level Parallelism (TLP). An application can expose TLP through annotations that identify the parallel functions (i.e., tasks). To generate accelerators that efficiently execute concur- rent tasks, we need to solve several issues: devise a mechanism to support concurrent execution flows, exploit memory parallelism, and manage synchronization. To support concurrent execution flows, we introduce a novel adaptive controller. The adaptive controller is composed of a set of interacting control elements that independently manage the execution of a single operation or function call. These control elements check dependencies and resource constraints at runtime, enabling as soon as possible execution. To support parallel access to shared memories and synchronization, we introduce a novel Hierarchical Memory Interface (HMI). With respect to previous solutions, the proposed interface supports multi-ported memories and atomic memory operations, which commonly occur in parallel programming. Our framework can generate the hardware implementation of C functions by employing two different approaches, depending on its characteristics. If a function exposes TLP, then the framework generates hardware implementations based on the adaptive controller. Otherwise, the framework implements the function by exploiting a more conventional FSM approach, which is optimized for ILP exploitation. We evaluate our framework on a set of parallel applications, and show substantial performance improvements (average speedup of 4.7) with limited area over- heads (average area increase of 5.48 times).

Castellana, Vito G.↗
DOE OSTI2021

Strategic Energy Management Program Persistence and Cost Effectiveness An Analysis of the SEM Program Landscape

This study examines the relationship between strategic energy management (SEM) programs and their persistence and cost effectiveness, with analysis based on interview data from 24 SEM program administrators, SEM program evaluations, and other reports. The 80 interview questions focused on the topics of program design, energy savings, energy savings persistence, cost effectiveness, and customer SEM persistence. The generosity of interview respondents provided a wealth of data, resulting in a report of sufficient length to warrant inclusion of this brief guide of the report structure. The major sections are listed below with brief descriptions. Individual sections of this report are mainly stand-alone and do not require reading of other sections. As a result, there is some duplication between sections, but with differing levels of detail. Executive Summary: Presents three key conclusions of this work with a short description of potential actions to advance the understanding of each key finding. Brief Observations: Lists a large number of bulleted observations resulting from this research, arranged by the five major topic areas included in the interviews. Analysis details are provided in the Analysis of Interview Results section. Foundations for this Research: Provides an overview of SEM, SEM frameworks, SEM programs, the topics of persistence and cost effectiveness, and the focus of this research. Methodology: Details the approach and strategy of this research, providing background information relevant to the formulation of interview questions and the identification of which SEM programs to interview. Observations from Compiled Evaluations and Other Reports: Reports observations from the collection and analysis of program evaluations, annual reports, utility planning documents, and SEM-related white papers. This section, presented in bullet form, highlights challenges in data collection and ultimately a comparison of program practices as they pertain to persistence and cost effectiveness. Analysis of Interview Results: Presents detailed analysis of responses from SEM program administrators, arranged by the five major categories examined: program design, energy savings, energy savings persistence, cost effectiveness, and customer SEM persistence. Interview questions are generally grouped together into subsections when it makes sense to examine them together. SEM Programs Challenge Traditional Cost-Effectiveness Metrics: Details an analysis based on five key factors showing that applying traditional cost-effectiveness metrics to SEM programs is not straightforward. This invites the opportunity to consider whether traditional cost-effectiveness metrics are applicable to SEM programs, either individually or at large. Resolution of Research Hypotheses: Tabulates a set of hypotheses that were developed to address the fundamental nature of the research at hand. Analysis of responses to multiple questions informs an understanding of each hypothesis and can be used to better understand the SEM program environment at large.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Final Prototype Microreactor Transportation Safety Program

This report fulfills the fiscal year 2025 M2 Milestone M2AT-25PN0802042, Final Microreactor Transportation Safety Program Planning Framework. Microreactors are compact reactors capable of producing less than 50 megawatts of electrical energy. Typically, these reactors are factory-fabricated and designed to be easily transportable by truck, rail, vessel, or air. Microreactor designs often assume that the unit can be transported containing either unirradiated or irradiated fuel. Interest in microreactors is driven by several factors, including the need to generate power at remote locations, military installations, and facilities such as data centers, and in areas recovering from natural disasters.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Analysis of human performance differences between students and operators when using the Rancor Microworld simulator

Here, from within the umbrella of the Simplified Human Error Experimental Program (SHEEP) framework, this paper analyzes human performance differences between professional and student operators when using a simplified simulator (i.e., Rancor Microworld). This paper represents a crucial step in understanding the fidelity of the simplified simulators and student operators within the SHEEP study. This paper explores a randomized factorial experimental design that features two independent variables: participant type and event class. Six human performance measurements are considered in the experiment. The experiment is conducted using 20 professional reactor operators employed at actual nuclear power plants (NPPs), along with 20 trained students. The experimental data are analyzed via statistical analysis methods. Finally, this paper examines the differences in human performance between actual operators and students when using Rancor Microworld.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Optimal management of electric hotel loads in mild hybrid heavy duty truck

Here, the problem of engine idling for heavy-duty trucks has been under study for decades with Auxiliary Power Units (APUs) and Truck Stop Electrification (TSE) as the most compelling solutions. With the electrification of trucks approaching feasibility in terms of cost-effective technology, hybridization offers another “degree of freedom” to tackle the problem. Here, this work aims at exploiting a battery pack of a 48 V mild-hybrid heavy-duty truck to store sufficient onboard energy for powering the auxiliary loads during the hoteling. This problem is not trivial, as the battery packs typically cannot recover the entire energy required through regeneration alone; hence an optimal energy management strategy needs to be employed to charge the battery through the engine during drive operation. This strategy optimizes powertrain performances among the four modes: (i) Engine of Coasting (EOC), (ii) Regeneration by braking, (iii) Regeneration by engine, and (iv) engine idling. This paper presents the development of a Dynamic Programming (DP) framework that employs a multi-objective cost function to minimize the fuel consumption and maximize the regeneration using the above-mentioned four modes. A typical heavy-duty truck drive cycle is used to represent the drive phase, with mandatory hoteling stops as per regulations. A comprehensive powertrain model is developed using validated components’ model. The DP employs two state variables: battery State-of-Charge (SOC) and engine mode, and three control inputs: (i) the engine ON–OFF state, (ii) clutch engagement state, and (iii) power request at the Electric Machine (EM) for calculating optimal SOC trajectory. The framework also tackles rapid engine ON–OFF scenarios to avoid the challenges associated with DP and the compromises in fuel cost with those approaches. Finally, the effectiveness of the proposed framework is tested for potential fuel savings on two different battery packs by performing the full cycle simulations. The results show 6.47% of fuel consumption reduction as compared to traditional APU-based heavy-duty truck.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

An Ab Initio Multiple Cloning Method for Non-Adiabatic Excited-State Molecular Dynamics in NWChem

The recently developed ab-initio multiple cloning (AIMC) approach based on the multicongurational Ehrenfest (MCE) method provides a powerful and accurate way of describing the excited-state dynamics of molecular systems. The AIMC method is a controlled approximation to non-adiabatic dynamics with a particular strength in the proper description of decoherence effects due to branching of vibrational wavepackets at a level crossing. In this work, we report a new implementation of the AIMC algorithm in the open source NWChem computational chemistry program. The framework combines linear-response time-dependent density functional theory with Ehrenfest mean-eld theory to determine the equations of motion for classical trajectories. The multi-dimensional wave function is decomposed into a superposition of Gaussian coherent states guided by Ehrenfest trajectories (i.e., MCE approach), which can clone with fully quantum mechanical amplitudes and phases. By using an efficient time-derivative based non-adiabatic coupling approach within the AIMC method, all observable are calculated on-the-y in the non-adiabatic molecular dynamics process. As a representative example, we apply our implementation to study the ultrafast photoinduced electronic and vibrational energy transfer in a pyridine molecule. The effects of the cloning procedure on electronic and vibrational coherence, relaxation and unidirectional energy transfer are discussed. This new AIMC implementation provides a high-level non-adiabatic molecular dynamics framework for simulating photoexcited dynamics in complex molecular systems and experimentally relevant ultrafast spectroscopic probes, such as nonlinear coherent optical and X-ray signals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Multiscale evolution of charmed particles in a nuclear medium

Parton energy-momentum exchange with the quark gluon plasma (QGP) is a multiscale problem. In this work, we calculate the interaction of charm quarks with the QGP within the higher twist formalism at high virtuality and high energy using the Modular All Twist Transverse-scattering Elastic-drag and Radiation (MATTER) model, while the low-virtuality and high-energy portion is treated via a linearized Boltzmann transport formalism. Coherence effect that reduces the medium-induced emission rate in the MATTER model is also taken into account through a virtuality-dependent qˆ, leaving the simultaneous dependence of qˆ on heavy quark mass and virtuality for future studies. The interplay between these two formalisms is studied phenomenologically and used to produce a first description of the D-meson and charged hadron nuclear modification factor R AA across multiple centralities. As a result, all calculations were carried out utilizing the Jet Energy-loss Tomography with a Statistically and Computationally Advanced Program Envelope framework.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Enabling Pulse-level Programming, Compilation, and Execution in XACC

Noisy gate-model quantum processing units (QPUs) are currently available from vendors over the cloud, and digital quantum programming approaches exist to run low-depth circuits on physical hardware. These digital representations are ultimately lowered to pulse-level instructions by vendor quantum control systems to affect unitary evolution representative of the submitted digital circuit. Vendors are beginning to open this pulse-level control system to the public via specified interfaces. Robust programming methodologies, software frameworks, and backend simulation technologies for this analog model of quantum computation will prove critical to advancing pulse-level control research and development. Prototypical use cases for this include error mitigation, optimal pulse control, and physics-inspired pulse construction. Here we present an extension to the XACC quantum-classical software framework that enables pulse-level programming for superconducting, gate-model quantum computers, and a novel, general, and extensible pulse-level simulation backend for XACC that scales on classical compute clusters via MPI. Our work enables custom backend Hamiltonian definitions and gate-level compilation to available pulses with a focus on performance and scalability. We end with a demonstration of this capability, and show how to use XACC for pertinent pulse-level programming tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Weapon Material Program: FY24 Annual Report

The Weapon Material Program (WMP) framework was started in July of Fiscal Year (FY) 2022, along with other Mission Support organizations. The first year was about building the organization with the right people, identifying needs, and developing a vision for expectations. It was also a year to move forward with new equipment and technology for weapon material processes. With numerous improvements, WMP is building world-class systems for production, warehousing, and analytical testing. FY 2023 was a year of development. The WMP was a new organization defining its identity, its focus, and its mission. At the end of FY 2023, WMP evaluated its current position and its immediate needs along with its future goals. The entire organization set out on this FY 2024 journey to success. The lack of funding, staffing, and visibility dramatically impacted weapon material operations, testing, and qualifications. This neglect required numerous areas to be addressed and improvement plans to be developed and implemented. WMP processes, procedures, and overall business operations were dramatically in need of updating, revision, and formal documentation. This included all areas: technology, equipment, facility modifications/upgrades, and testing improvements. To ensure organizational improvement and forward momentum in FY 2024, WMP executed a multi-faceted strategic vision. Action items included the following: • Filling open positions with capable personnel who would contribute to a more robust organization • Establishing more formal operations and problem-solving techniques • Improving departmental procedures to align with expanding scope • Improving training • Establishing collaboration meetings with other departments/organizations • Focusing on the importance of identifying and mitigating concerns with At-Risk Materials (@RM) • Leading modernization eff orts for Blending and Packaging (B&P) We are on the verge of a transformational improvement in all of our processes in support of the mission. The following area achievements outlined in this report reflect the hard work toward achieving the goal of “being the material Subject Matter Experts in the nuclear enterprise”.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗