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DOE OSTI2024

Machine Learning Enhanced Development of Functionally Graded Materials Enabled by Directed Energy Deposition

The ability to functionally grade materials provides designers with a new dimension of design flexibility that can be leveraged to improve functionality, reduce cost, or improve efficiency in a wide range of applications. This program was specifically focused on FGMs for hot and harsh gas path environments. These environments are common for the hot sections of jet engines and gas turbines, where parts undergo high temperature and mechanical loads in a corrosive environment. Expensive high γ' strengthened Ni superalloys such as René 41 (R41) and René 80 (R80) are generally used exclusively for a whole part, although only a section of the part demands such superalloys. To minimize cost, low/no γ' strengthened Ni superalloys such as Inconel 718 (INC718) could be used at less-demanding sections of the part could be welded to the high γ' strengthened Ni superalloys. However, the welding typically is a failure site due to the low durability at the welding interface. Functionally grading provides a welding alternative that can allow cost reduction without sacrificing mechanical performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Coordinated Planning Strategy for Integrated Energy Systems in a District Energy Sector

With the ever-growing integration of diverse distributed energy resources, modern district energy sectors are transitioning into integrated energy systems (IESs), which generally consist of various energy carriers such as electric power, natural gas, and heat. Instead of modeling individual energy carriers, the emergence of IESs requires comprehensive consideration of all involved energy systems in both planning and operation phases. This paper proposes a comprehensive planning strategy for a district energy sector to address the challenges of IES planning considering the coupling of power, gas, and heat systems. The proposed planning model contains an operational module that develops a steady-state optimal multi-energy flow (OMEF) for the IES considered and a multi-stage expansion module that optimizes the investment decisions. To efficiently solve the proposed planning model, which is formulated as a mixed-integer nonlinear programming problem, an improved generalized Benders decomposition algorithm that utilizes dynamic dual multipliers to improve the convergence speed is employed. The effectiveness of the proposed planning model and the feasibility of the improved Benders decomposition algorithm are verified in case studies.

coordinated planning↗

DOE OSTI2021

Opportunities for DOE National Laboratory-led QuantISED Experiments

A subset of QuantISED Sensor PIs met virtually on May 26, 2020 to discuss a response to a charge by the DOE Office of High Energy Physics. In this document, we summarize the QuantISED sensor community discussion, including a consideration of HEP science enabled by quantum sensors, describing the distinction between Quantum 1.0 and Quantum 2.0, and discussing synergies/complementarity with the new DOE NQI centers and with research supported by other SC offices. Quantum 2.0 advances in sensor technology offer many opportunities and new approaches for HEP experiments. The DOE HEP QuantISED program could support a portfolio of small experiments based on these advances. QuantISED experiments could use sensor technologies that exemplify Quantum 2.0 breakthroughs. They would strive to achieve new HEP science results, while possibly spinning off other domain science applications or serving as pathfinders for future HEP science targets. QuantISED experiments should be led by a DOE laboratory, to take advantage of laboratory technical resources, infrastructure, and expertise in the safe and efficient construction, operation, and review of experiments. The QuantISED PIs emphasized that the quest for HEP science results under the QuantISED program is distinct from the ongoing DOE HEP programs on the energy, intensity, and cosmic frontiers. There is robust evidence for the existence of particles and phenomena beyond the Standard Model, including dark matter, dark energy, quantum gravity, and new physics responsible for neutrino masses, cosmic inflation, and the cosmic preference for matter over antimatter. Where is this physics and how do we find it? The QuantISED program can exploit new capabilities provided by quantum technology to probe these kinds of science questions in new ways and over a broader range of science parameters than can be achieved with conventional techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2013

Commercial Building Energy Asset Score Program Overview and Technical Protocol (Version 1.1)

The U.S. Department of Energy (DOE) is developing a voluntary national scoring system for commercial buildings to help building owners and managers assess a building’s energy-related systems independent of operations. The goal of the score is to facilitate cost-effective investment in energy efficiency improvements of commercial buildings. The system, known as the Commercial Building Energy Asset Score, will allow building owners and managers to compare their building infrastructure against peers and track building upgrades over time. The system will also help other building stakeholders (e.g., building investors, tenants, financiers, and appraisers) understand the relative efficiency of different buildings in a way that is independent from operations and occupancy. This report outlines the technical protocol used to generate the energy asset score, explains the scoring methodology, and provides additional details regarding the energy asset scoring tool. The alternative methods that were considered prior to developing the current approach are described in the Program Overview and Technical Protocol Version 1.0.

Building Energy Use↗

DOE OSTI2014

Multifunctional Catalysts to Synthesize and Utilize Energy Carriers

The central role and critical importance of catalysis in a future based on sustainability, together with the insight that developments have to be knowledge-based have motivated significant efforts to better understand catalyzed processes and to develop new catalytic routes from this knowledge. Overall, three main energy carriers are used worldwide, carbon (and hydrocarbons), hydrogen, and electrons. Conventionally, the stored energy is accessed by oxidizing carbon and hydrogen, forming O-H and C-O bonds and performing work with the produced heat or electricity. Conversely, to synthesize energy carriers sustainably, it is consequently required to reverse the direction, i.e., to break C-O and O-H bonds and form C-C, C-H and H-H bonds. To address these challenges, PNNL’s BES-sponsored program comprises three thrust areas with subtasks, focusing on the fundamentals of biomass conversion processes, direct and indirect CO2 reduction, and on elementary studies aimed at generating and using H2. Multi-functionality, i.e., the simultaneous interaction of more than one catalytically active site with the substrate is the key to achieving the atom and energy efficiency in individual steps. The combination of several types of these sites with carefully selected energetics and rate constants is used to generate complex catalysts able to enhance the rates of multistep processes. This short report summarizes recent results obtained in this BES-funded program.

Environmental Molecular Sciences Laboratory↗

NASA NTRS2013

Summary of the 2012 Inductive Pulsed Plasma Thruster Development and Testing Program

Inductive pulsed plasma thrusters are spacecraft propulsion devices in which energy is capacitively stored and then discharged through an inductive coil. While these devices have shown promise for operation at high efficiency on a range of propellants, many technical issues remain before they can be used in flight applications. A conical theta-pinch thruster geometry was fabricated and tested to investigate potential improvements in propellant utilization relative to more common, flat-plate planar coil designs. A capacitor charging system is used to permit repetitive discharging of thrusters at multiple cycles per second, with successful testing accomplished at a repetition-rate of 5 Hz at power levels of 0.9, 1.6, and 2.5 kW. The conical theta-pinch thruster geometry was tested at cone angles of 20deg, 38deg, and 60deg, with single-pulse operation at 500 J/pulse and repetitionrate operation with the 38deg model quantified through direct thrust measurement using a hanging pendulum thrust stand. A long-lifetime valve was designed and fabricated, and initial testing was performed to measure the valve response and quantify the leak rate at beginning-of-life. Subscale design and testing of a capacitor charging system required for operation on a spacecraft is reported, providing insights into the types of components needed in the circuit topology employed. On a spacecraft, this system would accept as input a lower voltage from the spacecraft DC bus and boost the output to the high voltage required to charge the capacitors of the thruster.

Polzin, K. A.↗

DOE OSTI2023

Verifying MCNP Models of the TEX High 240 Plutonium Benchmark

Computational modeling programs are invaluable tools that allow us to understand systems, safely develop new processes, and make reliable predictions about future designs. However, the effectiveness of these codes is limited by the degree to which their parameters match the real world. In the field of nuclear engineering, cross section data is one of these vital parameters. Accurate cross section data on important fissile and fissionable isotopes promotes the design of safer and more efficient fabrication, transportation, storage, and stockpiling of nuclear fuel. Unfortunately, there are knowledge gaps in data on key isotopes. In 2011, a multinational meeting hosted by the US Department of Energy Nuclear Criticality Safety Program ranked the priority of certain cross section data needs. In response, Lawrence Livermore National Lab (LLNL) designed the Thermal and Epithermal eXperiment (TEX) series of benchmark experiments. Benchmark experiments are used to validate current cross section data. They validate data by comparing the results of an actual experiment to the predicted results from a computational model. The data a benchmark applies to depends on the isotope and energy range the experiment’s neutron multiplication factor ( k eff ) is most sensitive to. The development and testing of the TEX High 240 Plutonium Benchmark will help validate 240 Pu cross section data. The configuration and materials of this benchmark are designed to be most sensitive to 240 Pu's intermediate energy range (from 0.625 ev to 100 keV ). MCNP® models of the assembly have been developed by LLNL and the results have been written in the final design report. In order for the discrepancies between benchmark models and experiments to be attributed to cross section inaccuracies, the accuracy of the models needs to be verified. The goal of this project is to verify of the results of LLNL's modeling by creating a new set of MCNP models and comparing the results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Models and Algorithms for Equilibrium Analysis of Mixed-Material Nucleic Acid Systems

Dynamic programming algorithms within the NUPACK software suite enable analysis of equilibrium base-pairing properties for complex and test tube ensembles containing arbitrary numbers of interacting nucleic acid strands. Currently, calculations are limited to single-material systems that are either all-RNA or all-DNA. Here, to enable analysis of mixed-material systems that are critical for modern applications in vitro, in situ, and in vivo, we develop physical models and dynamic programming algorithms that allow the material of the system to be specified at nucleotide resolution. Free energy parameter sets are constructed for both RNA/DNA and RNA/2'OMe-RNA mixed-material systems by combining available empirical mixed-material parameters with single-material parameter sets to enable treatment of the full complex and test tube ensembles. New dynamic programming recursions account for the material of each nucleotide throughout the recursive process. For a complex with N nucleotides, the mixed-material dynamic programming algorithms maintain the O(N 3 ) time complexity of the single-material algorithms, enabling efficient calculation of diverse physical quantities over complex and test tube ensembles (e.g., complex partition function, equilibrium complex concentrations, equilibrium base-pairing probabilities, minimum free energy secondary structure(s), and Boltzmann-sampled secondary structures) at a cost increase of roughly 2.0-3.5×. The results of existing single-material algorithms are exactly reproduced when applying the new mixed-material algorithms to single-material systems. Accuracy is significantly enhanced using mixed-material models and algorithms to predict RNA/DNA and RNA/2'OMe-RNA duplex melting temperatures from the experimental literature as well as RNA/DNA melt profiles from new experiments. In conclusion, mixed-material analyses can be performed online using the NUPACK web app (www.nupack.org) or locally using the NUPACK Python module.

2′OMe-RNA↗

DOE OSTI2016

Development of an Efficient Approach to Perform Neutronics Simulations for Plutonium-238 Production

Conversion of 238Pu decay heat into usable electricity is imperative to power National Aeronautics and Space Administration (NASA) deep space exploration missions; however, the current stockpile of 238Pu is diminishing and the quality is less than ideal. In response, the US Department of Energy and NASA have undertaken a program to reestablish a domestic 238Pu production program and a technology demonstration sub-project has been initiated. Neutronics simulations for 238Pu production play a vital role in this project because the results guide reactor safety-basis, target design and optimization, and post-irradiation examination activities. A new, efficient neutronics simulation tool written in Python was developed to evaluate, with the highest fidelity possible with approved tools, the time-dependent nuclide evolution and heat deposition rates in 238Pu production targets irradiated in the High Flux Isotope Reactor (HFIR). The Python Activation and Heat Deposition Script (PAHDS) was developed specifically for experiment analysis in HFIR and couples the MCNP5 and SCALE 6.1.3 software quality assured tools to take advantage of an existing high-fidelity MCNP HFIR model, the most up-to-date ORIGEN code, and the most up-to-date nuclear data. Three cycle simulations were performed with PAHDS implementing ENDF/B-VII.0, ENDF/B-VII.1, and the Hybrid Library GPD-Rev0 cross-section libraries. The 238Pu production results were benchmarked against VESTA-obtained results and the impact of various cross-section libraries on the calculated metrics were assessed.

depletion↗

DOE OSTI2026

Energy Leaders: The Catalyst for Strategic Energy Management

This study investigates the crucial role energy leaders play in driving strategic energy management (SEM) and accelerating cost savings within a manufacturing organization and consequently, the industrial sector. Whereas energy efficiency can be seen as an innovative business practice with irrefutable cost benefits, its effective implementation requires strategic leadership and a structured approach. This research analyzes data collected from 120 participants representing 71 companies attending the Energy Bootcamp events organized by the U.S. Department of Energy’s (DOE) Better Plants program. The collected data focused on the state of SEM implementation, the presence and responsibilities of energy leaders, and the formation and function of energy teams. The findings reveal a significant gap between the perceived importance of SEM and its actual adoption, highlighting the need for strong leadership to drive behavioral changes by championing energy efficiency initiatives. Results indicate that effective energy leaders possess a diverse skill set, including the ability to secure top management buy-in, foster a culture of energy consciousness, and collaborate across departments. This study emphasizes the importance of empowering energy leaders with clearly defined roles and responsibilities as well as the authority to build and lead cross-functional energy teams. Furthermore, integrating energy management into existing organizational structures and leveraging readily available resources are identified as key factors for successful implementation. This research underscores how dedicated leadership and effective SEM practices help achieve industrial energy efficiency goals, providing practical insights for organizations seeking to improve performance and contribute to a resilient future.

energy leader↗

DOE OSTI2011

Business Case for Energy Efficiency in Support of Climate Change Mitigation, Economic and Societal Benefits in India

This study seeks to provide policymakers and other stakeholders with actionable information towards a road map for reducing energy consumption cost-effectively. We focus on individual end use equipment types (hereafter referred to as appliance groups) that might be the subject of policies - such as labels, energy performance standards, and incentives - to affect market transformation in the short term, and on high-efficiency technology options that are available today. the high efficiency or Business Case scenario is constructed around a model of cost-effective efficiency improvement. Our analysis demonstrates that a significant reduction in energy consumption and emissions is achievable at net negative cost, that is, as a profitable investment for consumers. Net savings are calculated assuming no additional costs to energy consumption such as carbon taxes. Savings relative to the base case as calculated in this way is often referred to as “economic savings potential”. So far, the Indian market has responded favorably to government efficiency initiatives, with Indian manufacturers producing a higher fraction of high-efficiency equipment than before program implementation. This study highlights both the financial benefit and the scope of potential impact for adopting this equipment, all of which is already readily available on the market. The approach of the study is to assess the impact of short-term actions on long-term impacts. “Short-term” market transformation is assumed to occur by 2015, while “long-term” energy demand reduction impacts are assessed in 2030. In the intervening years, most but not all of the equipment studied will turn over completely. The Business Case concentrates on technologies for which cost-effectiveness can be clearly demonstrated.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Marine energy supported multi-energy system planning and operation optimization for sustainable coastal community

The growing need for sustainable energy solutions in coastal areas necessitates the development of integrated systems that leverage abundant marine resources. In this study, a standalone Marine Energy Supported Multi-Energy System (MRE-MES) is designed for sustainable coastal community development, utilizing renewable marine resources, including offshore wind, wave, and solar energy, to address the energy needs of electricity, heat, freshwater, and hydrogen. The proposed MRE-MES incorporates a co-optimization model that simultaneously balances capacity planning and operational efficiency to minimize costs and environmental impacts. The system is tested under different renewable energy penetration levels and demand uncertainties, using a two-stage stochastic programming to account for variability in renewable resources and consumption needs. The experimental results indicate that in the optimal system capacity configuration, the percentage of total renewable energy generation is around 80 %, with or without capacity limitation constraints on PV, water tank, and hydrogen storage. Compared to the worst-case scenario in Monte Carlo experiments, two-stage stochastic optimization results in a more robust decision that effectively mitigates the risks posed by future uncertain demand conditions. In conclusion, the findings highlight the viability of marine energy for providing a resilient, comprehensive energy solution to coastal communities.

Capacity planning↗

DOE OSTI2022

Identifying Transient Candidates in the Dark Energy Survey Using Convolutional Neural Networks

The ability to discover new transient candidates via image differencing without direct human intervention is an important task in observational astronomy. For these kind of image classification problems, machine learning techniques such as Convolutional Neural Networks (CNNs) have shown remarkable success. In this work, we present the results of an automated transient candidate identification on images with CNNs for an extant data set from the Dark Energy Survey Supernova program, whose main focus was on using Type Ia supernovae for cosmology. By performing an architecture search of CNNs, we identify networks that efficiently select non-artifacts (e.g., supernovae, variable stars, AGN, etc.) from artifacts (image defects, mis-subtractions, etc.), achieving the efficiency of previous work performed with random Forests, without the need to expend any effort in feature identification. The CNNs also help us identify a subset of mislabeled images. Performing a relabeling of the images in this subset, the resulting classification with CNNs is significantly better than previous results, lowering the false positive rate by 27% at a fixed missed detection rate of 0.05.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2012

Healthy Zero Energy Buildings (HZEB) Program Interim Report on Cross Sectional Study of Contaminant Levels, Source Strengths, and Ventilation Rates in Retail Stores

The HZEB research program aims to generate information needed to develop new science-based commercial building ventilation rate (VR) standards that balance the dual objectives of increasing energy efficiency and maintaining acceptable indoor air quality. This interim report describes the preliminary results from one HZEB field study on retail stores. The primary purpose of this study is to estimate the whole-building source strengths of contaminant of concerns (COCs). This information is needed to determine the VRs necessary to maintain indoor concentrations of COCs below applicable health guidelines.The goal of this study is to identify contaminants in retail stores that should be controlled via ventilation, and to determine the minimum VRs that would satisfy the occupant health and odor criteria.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

2016 Building Technologies Office Peer Review Report

The 2016 Building Technologies Office Peer Review Report summarizes the feedback submitted by reviewers of the 67 BTO projects presented at the 2016 BTO Peer Review. The report presents an overview of the goals and activities under each technology program area, a summary of project scores for each program, and a brief analysis of general evaluation trends within each program area or its constituent subprograms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Energy Efficient Material Processing through Automated Process Monitoring and Controls

Smart manufacturing is bound to play a crucial role in reducing global energy consumption while accelerating economic development. This phenomenon is evident in advanced sensing technology developments, data analytics and machine learning/AI, automated controls, cloud computing, etc. The immediate opportunity for smart manufacturing is to improve the energy efficiency of manufacturing operations through innovations in processes and controls. The manufacturing industry still consumes about 30% of total global energy production, which is significant. This program focused on the recommendation of heterogeneous sensors to monitor the Chemical Vapor Infiltration (CVI) process parameters, states, and key performance indices and utilize cloud computing to sort and analyze the real-time data. Learning through data analytics helps guide the control parameters affecting energy usage. The target process in the program is the CVI process at the Honeywell South Bend facility, which is one of the most energy-intensive manufacturing industries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1986

Space solar cell research - Problems and potential

The value of a passive, maintenance-free, renewable energy source was immediately recognized in the early days of the space program, and the silicon solar cell, despite its infancy, was quickly pressed into service. Efficiencies of those early space solar arrays were low, and lifetimes shorter than hoped for, but within a decade significant advances had been made in both areas. Better performance was achieved because of a variety of factors, ranging from improvements in silicon single crystal material, to better device designs, to a better understanding of the factors that affect the performance of a solar cell in space. Chief among the latter, particularly for the mid-to-high altitude (HEO) and geosynchronous (GEO) orbits, are the effects of the naturally occurring particulate radiation environment. Although not as broadly important to the photovoltaic community at large as increased efficiency, the topic of radiation damage is critically important to use of solar cells in space, and is a major component of the NASA research program in space photovoltaics. This paper will give a brief overview of some of the opportunities and challenges for space photovoltaic applications, and will discuss some of the current reseach directed at achieving high efficiency and controlling the effects of radiation damage in space solar cells.

Flood, Dennis J.↗