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DOE OSTI2023

Sustainable Materials Selection in Manufactured Products: A Framework for Design-Integrated Life Cycle Thinking with Case Studies

Materials selection can provide a major opportunity to improve the environmental performance of manufactured products. Substitution of conventional materials with eco-friendly options can lower a product's environmental impact while still meeting key application requirements. A prerequisite for sustainability-informed decision-making is that relevant data and information are available for all materials being considered. Here we outline examples of the types and sources of data needed; and we explore key considerations for sustainable materials selection through a series of practical, cross-sectoral case studies.

36 MATERIALS SCIENCE↗

DOE OSTI2026

An Educational Program on Concentrated Solar Power and Heliostats for Power Generation and Industrial Processes

The objective of this project was to design and implement a comprehensive educational and applied research program in Concentrated Solar Thermal Power (CSTP) and heliostat technologies at Northeastern University. In alignment with the U.S. Department of Energy's Heliostat Consortium (HelioCon) goals, the project aimed to expand student and public understanding of CSTP systems while simultaneously contributing to workforce development and the broader decarbonization strategy. A particular emphasis was placed on integrating hands-on student design projects and publicly disseminating educational content relevant to CSTP systems. The project addressed a critical gap in renewable energy education: CSTP and heliostats, despite their importance in utility-scale solar energy, are rarely included in standard mechanical engineering programs. This project established new pathways for students to engage with the topic through the creation of a 4-credit graduate/senior elective course, development of five industry-facing short courses, and the inclusion of CSTP-based capstone design projects. Over two academic years, 36 students across six senior design teams developed and tested technologies such as deformable heliostats, beacon-based tracking systems, and solar-powered pyrolizers for biomass-to-biochar conversion. Concurrently, 30 undergraduate and graduate students were enrolled in the new academic course centered around CSTP principles. To ensure the relevance and accessibility of the short course content, the project team engaged with industry professionals, technical policy stakeholders, and potential course participants through structured surveys and informal consultations. Feedback from 28 respondents guided the structure, length, and delivery format of the courses - resulting in a modular design broken into five workshops. The feedback emphasized the need for flexible, asynchronous delivery and practical case studies, particularly in areas such as heliostat control, thermal storage, and solar fuel production. This engagement helped align the courses with the evolving knowledge demands of the renewable energy workforce and ensured that participants from both technical and policy backgrounds could meaningfully benefit from the material. The research and educational activities advanced the understanding of heliostat control systems, optical performance under misalignment, and thermal system integration in solar-driven pyrolysis applications. Methods and designs explored in this project proved to be both technically effective and economically feasible at the lab scale. Prototypes were constructed using commercially available components and custom-fabricated elements, demonstrating that meaningful performance improvements can be achieved with modest material and fabrication costs, supporting the feasibility of student-led research in this field. The public benefit of this project is twofold. First, it cultivates a pipeline of engineers trained to be familiar with CSTP principles, an essential workforce need identified by the Department of Energy for achieving its 2030 cost and deployment targets. Second, it contributes openly accessible educational materials, course content, and experimental frameworks to the broader community, enabling other institutions to adopt or adapt similar programming. Through outreach activities, curriculum integration, and technical exposure, this project contributes to a more informed and capable renewable energy workforce while supporting innovation in heliostat and CSTP system design. A new technical report is being prepared to document the development of the course and its outcomes, with plans to publish it in the ASME Open Access Journal of Engineering to ensure global accessibility, free of cost.

14 SOLAR ENERGY↗

DOE OSTI2021

A Mixed-Method Design Approach for Empirically Based Selection of Unbiased Data Annotators

Implicit bias embedded in the annotated data is by far the greatest impediment in the effectual use of supervised machine learning models in tasks involving race, ethics, and geopolitical polarization. For societal good and demonstrable positive impact on wider society, it is paramount to carefully select data annotators and rigorously validate the annotation process. Current approaches to selecting annotators are not sufficiently grounded in scientific principles and are limited at the policy-guidance level, thereby rendering them unusable for machine learning practitioners. This work proposes a new approach based on the mixed-methods design that is functional, adaptable, and simpler to implement in selecting unbiased annotators for any machine learning problem. By demonstrating it on a real-world geopolitical problem, we also identified and ranked key inane profile characteristics towards an empirically-based selection of unbiased data annotators.

Thakur, Gautam Malviya↗

NASA NTRS2014

Mars Sample Return Using Commercial Capabilities: Mission Architecture Overview

Mars Sample Return (MSR) is the highest priority science mission for the next decade as recommended by the recent Decadal Survey of Planetary Science. This paper presents an overview of a feasibility study for an MSR mission. The objective of the study was to determine whether emerging commercial capabilities can be used to reduce the number of mission systems and launches required to return the samples, with the goal of reducing mission cost. We report the feasibility of a complete and closed MSR mission design using the following scenario that covers three synodic launch opportunities, beginning with the 2022 opportunity: A Falcon Heavy injects a SpaceX Red Dragon capsule and trunk onto a Trans Mars Injection (TMI) trajectory. The capsule is modified to carry all the hardware needed to return samples collected on Mars including a Mars Ascent Vehicle (MAV), an Earth Return Vehicle (ERV), and hardware to transfer a sample collected in a previously landed rover mission to the ERV. The Red Dragon descends to land on the surface of Mars using Super Sonic Retro Propulsion (SSRP). After previously collected samples are transferred to the ERV, the single-stage MAV launches the ERV from the surface of Mars. The MAV uses a storable liquid bi-propellant propulsion system to deliver the ERV to a Mars phasing orbit. After a brief phasing period, the ERV, which also uses a storable bi-propellant system, performs a Trans Earth Injection (TEI) burn. Upon arrival at Earth, the ERV performs Earth and lunar swing-bys and is placed into a lunar trailing circular orbit - an Earth orbit, at lunar distance. A later mission, using Dragon and launched by a Falcon Heavy, performs a rendezvous with the ERV in the lunar trailing orbit, retrieves the sample container and breaks the chain of contact with Mars by transferring the sample into a sterile and secure container. With the sample contained, the retrieving spacecraft makes a controlled Earth re-entry preventing any unintended release of pristine martian materials into the Earth's biosphere. The analysis methods employed standard and specialized aerospace engineering tools. Mission system elements were analyzed with either direct techniques or by using parametric mass estimating relationships (MERs). The architecture was iterated until overall mission convergence was achieved on at least one path. Subsystems analyzed in this study include support structures, power system, nose fairing, thermal insulation, actuation devices, MAV exhaust venting, and GN&C. Best practice application of loads, mass growth contingencies, and resource margins were used. For Falcon Heavy capabilities and Dragon subsystems we utilized publically available data from SpaceX, published analyses from other sources, as well as our own engineering and aerodynamic estimates. Earth Launch mass is under 11 mt, which is within the estimated capability of a Falcon Heavy, with margin. Total entry masses between 7 and 10 mt were considered with closure occurring between 9 and 10 mt. Propellant mass fractions for each major phase of the EDL - Entry, Terminal Descent, and Hazard Avoidance - have been derived. An assessment of the effect of the entry conditions on the thermal protection system (TPS), currently in use for Dragon missions, shows no significant stressors. A useful payload mass of 2.0 mt is provided and includes mass growth allowances for the MAV, the ERV, and mission unique equipment. We also report options for the MAV and ERV, including propulsion systems, crewed versus robotic retrieval mission, as well as direct Earth entry. International planetary protection policies as well as verifiable means of compliance will have a large impact on any MSR mission design. We identify areas within our architecture where such impacts occur. We also describe preliminary compliance measures that will be the subject of future work. This work shows that emerging commercial capabilities as well as new methodologies can be used to efficiently support an important planetary science objective. The work also has applications for human exploration missions that use propulsive EDL techniques

Red Dragon↗

DOE OSTI2024

Research Priorities and Opportunities in U.S. Wholesale Electricity Markets: Market Design under Deep Decarbonization

This report provides a comprehensive review of challenges, research needs, and potential solutions for competitive wholesale electricity market design in deeply decarbonized power systems. We provide context regarding how competitive wholesale electricity markets can evolve in a longer-term perspective to ensure that they still operate efficiently throughout the transition to a deeply decarbonized future. We organize the discussion across seven topics: operational reliability, emerging technology integration, adequacy and resilience, price formation, interactions across transmission and distribution systems, transmission planning, achieving clean energy objectives, and challenges associated with cost-effectively achieving clean energy objectives. In each section we first identify key associated challenges before proposing a set of corresponding solutions and research needs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2013

Mars Sample Return Using Commercial Capabilities: Mission Architecture Overview

Mars Sample Return (MSR) is the highest priority science mission for the next decade as recommended by the recent Decadal Survey of Planetary Science. This paper presents an overview of a feasibility study for a MSR mission. The objective of the study was to determine whether emerging commercial capabilities can be used to reduce the number of mission systems and launches required to return the samples, with the goal of reducing mission cost. The major element required for the MSR mission are described and include an integration of the emerging commercial capabilities with small spacecraft design techniques; new utilizations of traditional aerospace technologies; and recent technological developments. We report the feasibility of a complete and closed MSR mission design using the following scenario that covers three synodic launch opportunities, beginning with the 2022 opportunity: A Falcon Heavy injects a SpaceX Red Dragon capsule and trunk onto a Trans Mars Injection (TMI) trajectory. The capsule is modified to carry all the hardware needed to return samples collected on Mars including a Mars Ascent Vehicle (MAV); an Earth Return Vehicle (ERV); and hardware to transfer a sample collected in a previously landed rover mission to the ERV. The Red Dragon descends to land on the surface of Mars using Supersonic Retro Propulsion (SRP). After previously collected samples are transferred to the ERV, the single-stage MAV launches the ERV from the surface of Mars to a Mars phasing orbit. The MAV uses a storable liquid, pump fed bi-propellant propulsion system. After a brief phasing period, the ERV, which also uses a storable bi-propellant system, performs a Trans Earth Injection (TEI) burn. Once near Earth the ERV performs Earth and lunar swing-bys and is placed into a Lunar Trailing Orbit (LTO0 - an Earth orbit, at lunar distance. A later mission, using a Dragon and launched by a Falcon Heavy, performs a rendezvous with the ERV in the lunar trailing orbit, retrieves the sample container and breaks the chain of contact with Mars by transferring the sample into a sterile and secure container. With the sample contained, the retrieving spacecraft, makes a controlled Earth re-entry preventing any unintended release of pristine Martian materials into the Earth's biosphere. Other capsule type vehicles and associated launchers may be applicable. The analysis methods employed standard and specialized aerospace engineering tools. Mission system elements were analyzed with either direct techniques or by using parametric mass estimating relationships (MERs). The architecture was iterated until overall mission convergence was achieved on at least one path. Subsystems analyzed in this study include support structures, power system, nose fairing, thermal insulation, actuation devices, MAV exhaust venting, and GN&C. Best practice application of loads, mass growth contingencies, and resource margins were used. For Falcon Heavy capabilities and Dragon subsystems we utilized publically available data from SpaceX; published analyses from other sources; as well as our own engineering and aerodynamic estimates. Earth Launch mass is under 11 mt, which is within the estimated capability of a Falcon Heavy, with margin. Total entry masses between 7 and 10 mt were considered with closure occurring between 9 and 10 mt. Propellant mass fractions for each major phase of the EDL - Entry, Terminal Descent, and Hazard Avoidance - have been derived. An assessment of the entry conditions on the thermal protection system (TPS), currently in use for Dragon missions, has been made. And shows no significant stressors. A useful mass of 2.0 mt is provided and includes mass growth allowances for the MAV, the ERV, and mission unique equipment. We also report on alternate propellant options for the MAV and options for the ERV, including propulsion systems; crewed versus robotic retrieval mission; as well as direct Earth entry. International Planetary Protection Policies as well as verifiable means of compliance will have a large impact on any MSR mission design. We identify areas within our architecture where such impacts occur. This work shows that emerging commercial capabilities can be used to effectively integrated into a mission to achieve an important planetary science objective.

Mars Sample Return↗

DOE OSTI2022

Federated Learning and Differential Privacy: What might AI-Enhanced co-design of microelectronics learn?

Data is a valuable commodity, and it is often dispersed over multiple entities. Sharing data or models created from the data is not simple due to concerns regarding security, privacy, ownership, and model inversion. This limitation in sharing can hinder model training and development. Federated learning can enable data or model sharing across multiple entities that control local data without having to share or exchange the data themselves. Differential privacy is a conceptual framework that brings strong mathematical guarantee for privacy protection and helps provide a quantifiable privacy guarantee to any data or models shared. The concepts of federated learning and differential privacy are introduced along with possible connections. Lastly, some open discussion topics on how federated learning and differential privacy can tied to AI-Enhanced co-design of microelectronics are highlighted.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Herding Cats: Firm Non-Compliance in China’s Industrial Energy Efficiency Program

Here we study firm responses to a large-scale energy efficiency program in China, focusing on the quality of reporting and compliance outcomes. Using statistical methods to detect data manipulation in compliance reports, we find evidence that firms deliberately exaggerated performance during the first phase of the program (2006-2010), suggesting the high compliance rate was overstated. In its second phase (2011-2015), the number of firms in the program expanded by an order of magnitude, and the compliance rate decreased. We develop a simple model to show how the observed increase in non-compliance is consistent with reduced misreporting. Statistical tests find no evidence of manipulation in the second phase. Larger firms, especially those not controlled by the state, and firms in cities with relatively low growth were more likely to report non-compliance, which suggests a role for state control and local protectionism in shaping compliance decisions. Based on our findings, we offer several lessons for future program design.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

VC3: Virtual Clusters for Community Computation (Final Technical Report)

A traditional HPC computing facility provides a large amount of computing power but has a fixed environment designed to satisfy local needs. This makes it very challenging for users to deploy complex applications that span multiple sites and require specific application software, scheduling middleware, or sharing policies. This project addressed many of these challenges by making it possible for researchers to easily aggregate and share resources, install custom software environments, and deploy clustering frameworks across multiple HPC facilities through the concept of “virtual clusters”. We designed and implemented a prototype virtual cluster facility that enabled unprivileged users to create dynamic aggregations of computing power across multiple sites, deployed with custom middleware and complex software dependencies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

VC3: Virtual Clusters for Community Computation

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Building Envelope Characteristics in Cold Climates

Prescriptive guidelines for thermal insulation in the design of buildings in cold climates have traditionally been derived by a holistic consideration of climatic factors, energy policy, environmental policy, and economics. The differences in thermal barrier requirements in buildings across the arctic and subarctic regions of the world are influenced as much by the differing priorities of the governing bodies that set these requirements as by actual physical demands and conditions. Usually, national requirements for building envelope characteristics such as thermal insulation values, building envelope airtightness, vapor permeability, building mass, and detailing are based on economics, durability, and environmental considerations. Consideration of thermal energy system resilience provides a new paradigm through which to view the optimization of these parameters. The paper describes specifics of construction in cold climates; summarizes best practice requirements for the building envelope characteristics for buildings located in cold and arctic climate of the United States, Canada, and Scandinavian countries; provides some details illustrating how to implement these requirements; and compares the effects of different levels of building envelope efficiency and building mass on indoor air temperature decay when heat supply is interrupted. The paper also presents results from experts' discussions during the consultation forum "Thermal Energy Systems Resilience in Cold/Arctic Climates" (ERDC 2020) and research conducted under the IEA EBC Annex 73, the Environmental Security Technology Certification Program (ESTCP) Project "Technologies Integration to Achieve Resilient, Low-Energy Military Installations," and U.S. Army Program project 633734T1500 under Military Engineering Technology Demonstration. The paper complements the Cold-Climate Design Guide (ASHRAE 2015) with a focus on the resilience of thermal energy systems.

Arctic↗

NASA NTRS2008

Constellation Program Life-cycle Cost Analysis Model (LCAM)

The Constellation Program (CxP) is NASA's effort to replace the Space Shuttle, return humans to the moon, and prepare for a human mission to Mars. The major elements of the Constellation Lunar sortie design reference mission architecture are shown. Unlike the Apollo Program of the 1960's, affordability is a major concern of United States policy makers and NASA management. To measure Constellation affordability, a total ownership cost life-cycle parametric cost estimating capability is required. This capability is being developed by the Constellation Systems Engineering and Integration (SE&I) Directorate, and is called the Lifecycle Cost Analysis Model (LCAM). The requirements for LCAM are based on the need to have a parametric estimating capability in order to do top-level program analysis, evaluate design alternatives, and explore options for future systems. By estimating the total cost of ownership within the context of the planned Constellation budget, LCAM can provide Program and NASA management with the cost data necessary to identify the most affordable alternatives. LCAM is also a key component of the Integrated Program Model (IPM), an SE&I developed capability that combines parametric sizing tools with cost, schedule, and risk models to perform program analysis. LCAM is used in the generation of cost estimates for system level trades and analyses. It draws upon the legacy of previous architecture level cost models, such as the Exploration Systems Mission Directorate (ESMD) Architecture Cost Model (ARCOM) developed for Simulation Based Acquisition (SBA), and ATLAS. LCAM is used to support requirements and design trade studies by calculating changes in cost relative to a baseline option cost. Estimated costs are generally low fidelity to accommodate available input data and available cost estimating relationships (CERs). LCAM is capable of interfacing with the Integrated Program Model to provide the cost estimating capability for that suite of tools.

Prince, Andy↗

DOE OSTI2024

Towards Cost-Competitive Microreactors

To assess the cost competitiveness of microreactors, a new tool integrating reactor design calculations with economic models was developed. Using detailed cost data and design specifications from the MARVEL project (85 kWth), the tool estimates costs for a more representative commercial microreactor (20 MWth). The LCOE for a 20 MWth MARVEL-like reactor is estimated at $236/MWh, with an overnight cost of about $12,000/kW (excluding fuel). Mass production could reduce costs by 70%, making the 10th unit cost around $3,700/kWe, which is economically competitive. The new neutronics-economics coupling tool also enables studying the impact of the design parameters on the economic figures of merit. The impact of changing the enrichment and reactor capacity on the LCOE has been studied.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

A conceptual framework for residential energy security in the context of clean energy transitions

Energy security is a crucial aspect of human well-being. As climate change impacts become more evident, countries are constructing equitable, resilient, and sustainable clean energy transition policies to reduce emissions while ensuring energy security. Climate policies globally highlight the importance of national energy security. Furthermore, adequate and affordable access to household energy is also critical to the continued prioritization of climate mitigation. However, past energy security discussions within the broader climate research and policymaking community primarily focused on national-level energy supply as a critical metric of energy security. Less research has explored the potential implications of energy transitions for residential energy security, often focusing on a single dimension of residential energy security. Thus, we conduct a review of journal articles and governmental plans to develop a conceptual framework of residential energy security and facilitate communication among researchers and policymakers. The framework is designed around four foundational pillars, five metrics measuring residential energy security, and seven drivers influencing the metrics. Additionally, we provide policy examples to show how this framework can be applied to inform decision-making. Thus, this paper makes important contributions to the literature by (a) creating a framework to better understand the concept of energy security at the household level for future research and policy-relevant communications, (b) identifying gaps in the current literature, and (c) highlighting instances where aspects of residential energy security are discussed in policies and governmental plans, which help serve as guiding examples for future applications of our framework in the policymaking processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

Reinforcement Learning for Spacecraft Navigation & Environment Characterization in the Planar-Restricted Two-Body Problem

As science, exploration, and commercial space missions become increasingly complex, so does the need for efficient, autonomous, and integrated spacecraft navigation and operations techniques. Key operational functions, including data collection and transmission, environment characterization, systems constraints, human factors, and navigation, often are intertwined and conflicted. Deep Reinforcement Learning (DRL) offers a framework for addressing integrated spacecraft navigation and planning in an uncertain dynamical environment. The goal of this study is to evaluate the utility of DRL for integrated spacecraft navigation and planning. This is achieved by developing a simple environmental characterization training environment in the Planar-Restricted 2-Body Problem (PR2BP), establishing benchmarks and heuristic baselines, and designing a previously unstudied Markov Decision Process (MDP) formulation. This MDP formulation enables the spacecraft DRL agents to appropriately balance navigation and actuation capabilities. The resulting DRL-derived policy exceeds a random or untrained policy and meets or exceeds the level of performance of a heuristic without actuation. In the process, valuable intuition is gained about the problem with insight into how DRL methods could scale to increasingly more realistic scenarios, including net-work design and training architectures, efficient state space representations, and methods for encouraging exploration in a parametric action space, among others.

navigation↗

DOE OSTI2023

Exploring sustainable electricity system development pathways in South America’s MERCOSUR sub-region

South America has abundant natural water and energy resources, and exploiting these resources to achieve a clean energy future is central to the continent’s economic and sustainable development objectives for the next several decades. Designing pathways to achieving this clean energy future requires better understanding the structural, techno-economic, and policy forces that may influence the future development of the electricity sector in the region. Here, we focus on an interconnected electricity system of five South American countries – Argentina, Brazil, Chile, Paraguay, and Uruguay – which represent major electricity generation, consumption, and trade dynamics in the region. We explore the implications of various forces that could shape the future composition of the power sector in the sub-region, including: evolving renewable energy cost and performance, natural gas prices, cross-border interconnection facilities, early retirement of installed hydropower, and different decarbonization goals. We use a model framework based on a power system planning platform (GridPath) to co-optimize investment and operations of generation, storage, and transmission facilities out to 2050. Our results in a Reference scenario indicate that the electricity system can maintain a relatively clean energy portfolio by leveraging existing hydropower capacity and integrating increasingly cost-competitive wind and solar power. However, dependence on natural gas in the region is likely to remain high. A low-carbon electricity system can cost-effectively be achieved through policy interventions (e.g., renewable portfolio standards) and by diversifying investments in wind, solar, battery storage, and some new hydropower capacity. We also find that existing hydropower is critical for maintaining reliable future grid operations. Enhanced regional electricity trade, mostly based on existing interconnection capacities with nominal investment in new transmission, can significantly benefit the clean energy transition in the region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Extending Rucio with modern cloud storage support

Rucio is a software framework designed to facilitate scientific collaborations in efficiently organising, managing, and accessing extensive volumes of data through customizable policies. The framework enables data distribution across globally distributed locations and heterogeneous data centres, integrating various storage and network technologies into a unified federated entity. Rucio offers advanced features like distributed data recovery and adaptive replication, and it exhibits high scalability, modularity, and extensibility. Originally developed to meet the requirements of the high-energy physics experiment ATLAS, Rucio has been continuously expanded to support LHC experiments and diverse scientific communities. Recent R&D projects within these communities have evaluated the integration of both private and commercially-provided cloud storage systems, leading to the development of additional functionalities for seamless integration within Rucio. Furthermore, the underlying systems, FTS and GFAL/Davix, have been extended to cater to specific use cases. This contribution focuses on the technical aspects of this work, particularly the challenges encountered in building a generic interface for self-hosted cloud storage, such as MinIO or CEPH S3 Gateway, and established providers like Google Cloud Storage and Amazon Simple Storage Service. Additionally, the integration of decentralised clouds like SEAL is explored. Key aspects, including authentication and authorisation, direct and remote access, throughput and cost estimation, are highlighted, along with shared experiences in daily operations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Restoring Critical Loads In Resilient Distribution Systems using A Curriculum Learned Controller

In this paper, we propose a curriculum learned reinforcement learning (RL) controller to facilitate distribution system critical load restoration (CLR), leveraging RL's fast online response and its outstanding optimal sequential control capability. Like many grid control problems, CLR is complicated due to the large control action space and renewable uncertainty in a heavily constrained non-linear environment with strong intertemporal dependency. The nature of the problem oftentimes causes the RL policy to converge to a poor-performing local optimum if learned directly. To overcome this, we design a two-stage curriculum in which the RL agent will learn generation control and load restoration decision under different scenarios progressively. Via curriculum learning, the trained RL controller is expected to achieve a better control performance, with critical loads restored as rapidly and reliably as possible. Using the IEEE 13-bus test system, we illustrate the performance of the RL controller trained by the proposed curriculum-based method.

curriculum learning↗