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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Challenges for monitoring and data analytics in a leadership public data repository

The availability and disposition of data has assumed increasing importance in large-scale computational science. Data repositories are evolving to meet new classes of requirements: compliance with government access guidelines, support for reproducibility of experimental results, and long-term availability of data products. The Constellation public data repository at the Oak Ridge Leadership Computing Facility faces these issues while being situated in one of the most productive data centers in the world. While monitoring and operational data analysis are ingrained in the operation of the OLCF’s large-scale high performance computing platforms, data repositories do not have this history of support. Problems faced by Constellation range from data size (over 7 petabytes in current holdings) to analytic complexity (detailed curation is both absolutely necessary for many data sets and absolutely impossible for humans to accomplish in any practical manner) to deployment environment (OLCF storage resources are oriented toward the needs of the compute platforms). In this paper we describe some of the challenges for collecting monitoring and analytic data from a leadership public data repository. We also discuss various strategies we are pursuing in order to address these challenges, from manual data collection to plans for introducing machine learning-based curatorial techniques.

Widener, Patrick [ORNL] (ORCID:0000000258820816)↗
DOE OSTI2025

Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions

We discuss the challenges and propose research directions for using AI to revolutionize the development of high-performance computing (HPC) software. AI technologies, in particular large language models, have transformed every aspect of software development. For its part, HPC software is recognized as a highly specialized scientific field of its own. We discuss the challenges associated with leveraging state-of-the-art AI technologies to develop such a unique and niche class of software and outline our research directions in the two US Department of Energy–funded projects for advancing HPC Software via AI: Ellora and Durban.

Teranishi, Keita [ORNL] (ORCID:0000000166472690)↗
DOE OSTI2022

Challenges for unsupervised anomaly detection in particle physics

Anomaly detection relies on designing a score to determine whether a particular event is uncharacteristic of a given background distribution. One way to define a score is to use autoencoders, which rely on the ability to reconstruct certain types of data (background) but not others (signals). In this paper, we study some challenges associated with variational autoencoders, such as the dependence on hyperparameters and the metric used, in the context of anomalous signal (top and W) jets in a QCD background. We find that the hyperparameter choices strongly affect the network performance and that the optimal parameters for one signal are non-optimal for another. In exploring the networks, we uncover a connection between the latent space of a variational autoencoder trained using mean-squared-error and the optimal transport distances within the dataset. We then show that optimal transport distances to representative events in the background dataset can be used directly for anomaly detection, with performance comparable to the autoencoders. Whether using autoencoders or optimal transport distances for anomaly detection, we find that the choices that best represent the background are not necessarily best for signal identification. These challenges with unsupervised anomaly detection bolster the case for additional exploration of semi-supervised or alternative approaches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Additively manufactured heat exchangers: a review on opportunities and challenges

Heat Exchangers (HXs) are crucial engineering components for thermal management. The broad range of applications and the current limits of traditional manufacturing techniques has directed designers and researchers to utilize additive manufacturing (AM) technologies to open a new chapter in HXs design and development. AM has created a world of opportunity to redesign HXs in pioneering forms, shapes, and sizes. In other words, AM technologies provides significant opportunities to increase surface area to volume ratio in heat transfer devices. On the other hand, there are certain challenges to overcome in order to fully grasp the benefits of AM technologies. This thorough review study is different from other published review as it intends to highlight the challenges and opportunities in design and manufacturing of HXs. In addition, part of this study is dedicated to investigate the experimental characterization of additively manufactured HXs. Furthermore, the significant details associated with experimental characterization are normally overlooked in review studies.

42 ENGINEERING↗
DOE OSTI2026

MRV Challenge 3: velocity and passive scalar comparison in a 3D turbulent flow

The third iteration of a magnetic resonance velocimetry (MRV) challenge comparison activity consisting of 3D flow measurements for a turbulent flow in a water channel moving past centrally positioned cubic obstacles is reported. In this challenge iteration, MRV measurements are coupled with either temperature or concentration measurements to extend the diagnostic utility. Five research teams from around the world conducted the measurements on a single shared apparatus. The water channel included partial elements along the channel sidewalls that varied in height and precluded easy optical accessibility. In addition to a turbulent mainstream flow, a secondary flow entered the channel between the second and third cubic elements from a square injector hole at the channel bottom wall. The injector jet interacts with the mainstream flow and mixes turbulently as it advects downstream. For the selected flow regime and water solutions used as working fluids, the mixing of the higher temperature or concentration through the secondary flow with the mainstream flow satisfies the same dynamics so that both temperature and concentration fields behave as passive scalars and can be directly compared. The measurements are explained in detail by each participating team, and the results are interpolated onto a common grid and compared using line profiles, contour plots, and isosurfaces.

Benson, Mike [ORNL] (ORCID:000000023210116X)↗
DOE OSTI2025

Unique & challenging aspects of plutonium metal standards exchange program for actinide measurements

The Los Alamos National Laboratory exchange program is the only program of its kind for the distribution of plutonium (Pu) standards materials with a range of impurity contents to multiple laboratories for destructive measurements of elemental concentration. This paper discusses statistical methods used to address challenges in Pu metal exchange data by way of two case studies. Challenges include how to evaluate a data set when a large fraction of the values are minimum detection limits (MDLs), and how to determine potential outliers with limited in-formation on the true spread of the data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

GPS-supported smartphone app-based integrated travel diary and time-use data collection: challenges and lessons learned

Travel behaviour and time-use data are two vital data sources for travel demand modelling. Travel behaviour is traditionally collected through household travel surveys, enhanced by using GPS-supported smartphone apps for passive location data collection. However, recruiting individuals willing to install these apps with sustained motivation to continue participation has been a critical challenge. This paper shares insights from a travel and time-use data collection procedure in Chicago and Sydney using the Fourstep app. Social media platforms were utilised as a solution to recruit participants in Chicago, where an international market research company failed to accomplish the task. This paper also discusses the challenges we faced and suggests ways to overcome them, offering valuable guidance to researchers in recruiting participants for smartphone application-based data collection. It also offers an analysis of travel, time-use, and travel-based multitasking behaviours based on the data collected from the Chicago and Sydney samples.

GPS-supported smartphone apps↗
DOE OSTI2021

Challenges and Advances in Information Extraction from Scientific Literature: a Review

Scientific articles have long been the primary means of disseminating scientific discoveries. Over the centuries, valuable data and potentially groundbreaking insights have been collected and buried deep in the mountain of publications. In materials engineering, such data are spread across technical handbooks specification sheets, journal articles, and laboratory notebooks in myriad formats. Extracting information from papers on a large scale has been a tedious and time-consuming job to which few researchers have wanted to devote their limited time and effort, yet is an activity that is essential for modern data-driven design practices. However, in recent years, significant progress has been made by the computer science community on techniques for automated information extraction from free text. Yet, transformative application of these techniques to scientific literature remains elusive-due not to a lack of interest or effort but to technical and logistical challenges. Using the challenges in the materials science literature as a driving motivation, we review the gaps between state-of-the-art information extraction methods and the practical application of such methods to scientific texts, and offer a comprehensive overview of work that can be undertaken to close these gaps.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

AFRL Additive Manufacturing Modeling Series: Challenge 1, Characterization of Residual Strain Distribution in Additively-Manufactured Metal Parts Using Energy-Dispersive Diffraction

A machine component fabricated by additive manufacturing (AM) of metal powders often possesses steep residual stress gradients with significant magnitudes due to large temperature gradients that transpire within a localized area during fabrication. These processing-induced residual stresses can cause distortion of the part, and if they are of significant magnitude, they could induce cracking of the component, degrade printability, and/or diminish subsequent mechanical performance. The ability to predict these residual stresses imparted by AM is an important step in permeating AM technology for advanced manufacturing. Calibration and validation of AM process models used for prediction are, therefore, a critical step in understanding the origin and mitigating the challenges associated with residual stresses inherent to the AM process. In the present work, the residual strain distributions in components with simple geometries fabricated by a laser powder bed fusion (LBPF) process were characterized non-destructively using energy-dispersive X-ray diffraction in support of the US Air Force Research Laboratory Additive Manufacturing Modeling Challenge Series Groeber et al. (JOM 70:441-448, 2018). The measurement setup and approach are described in detail so that the data can be used as a benchmark to calibrate and validate models for the prediction of macro-scale residual stresses due to the LPBF process.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Outcomes and Conclusions from the 2022 AM Bench Measurements, Challenge Problems, Modeling Submissions, and Conference

The Additive Manufacturing Benchmark Test Series (AM Bench) provides rigorous measurement data for validating additive manufacturing (AM) simulations for a broad range of AM technologies and material systems. AM Bench includes extensive in situ and ex situ measurements, simulation challenges for the AM modeling community, and a corresponding conference series. In 2022, the second round of AM Bench measurements, challenge problems, and conference were completed, focusing primarily upon laser powder bed fusion (LPBF) processing of metals, and both material extrusion processing and vat photopolymerization of polymers. In all, more than 100 people from 10 National Institute of Standards and Technology (NIST) divisions and 21 additional organizations were directly involved in the AM Bench 2022 measurements, data management, and conference organization. The international AM community submitted 138 sets of blind modeling simulations for comparison with the in situ and ex situ measurements, up from 46 submissions for the first round of AM Bench in 2018. Analysis of these submissions provides valuable insight into current AM modeling capabilities. The AM Bench data are permanently archived and freely accessible online. The AM Bench conference also hosted an embedded workshop on qualification and certification of AM materials and components.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Physical, numerical, and computational challenges of modeling neutrino transport in core-collapse supernovae

The proposal that core collapse supernovae are neutrino driven is still the subject of active investigation more than 50 years after the seminal paper by Colgate and White. The modern version of this paradigm, which we owe to Wilson, proposes that the supernova shock wave is powered by neutrino heating, mediated by the absorption of electron-flavor neutrinos and antineutrinos emanating from the proto-neutron star surface, or neutrinosphere. Neutrino weak interactions with the stellar core fluid, the theory of which is still evolving, are flavor and energy dependent. The associated neutrino mean free paths extend over many orders of magnitude and are never always small relative to the stellar core radius. Thus, neutrinos are never always fluid like. Instead, a kinetic description of them in terms of distribution functions that determine the number density of neutrinos in the six-dimensional phase space of position, direction, and energy, for both neutrinos and antineutrinos of each flavor, or in terms of angular moments of these neutrino distributions that instead provide neutrino number densities in the four-dimensional phase-space subspace of position and energy, is needed. In turn, the computational challenge is twofold: (i) to map the kinetic equations governing the evolution of these distributions or moments onto discrete representations that are stable, accurate, and, perhaps most important, respect physical laws such as conservation of lepton number and energy and the Fermi–Dirac nature of neutrinos and (ii) to develop efficient, supercomputer-architecture-aware solution methods for the resultant nonlinear algebraic equations. In this review, we present the current state of the art in attempts to meet this challenge.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Peer-to-Peer Energy Systems for Connected Communities: A Review of Recent Advances and Emerging Challenges

After a century of relative stability of the electricity industry, extensive deployment of distributed energy resources and recent advances in computation and communication technologies have changed the nature of how we consume, trade, and apply energy. The power system is facing a transition from its traditional hierarchical structure to a more deregulated model by introducing new energy distribution models such as peer-to- peer (P2P) sharing for connected communities. The proven effectiveness of P2P sharing in benefiting both prosumers and the grid has been demonstrated in many studies and pilot projects. However, there is still no extensive implementation of such sharing models in today’s electricity markets. This paper aims to shed some light on this gap through a comprehensive overview of recent advances in the P2P energy system and an insightful discussion of the challenges that need to be addressed in order to establish P2P sharing as a viable energy management option in today’s electricity market. To this end, in this article, we provide some background on different aspects of P2P sharing. Then, we discuss advances in P2P sharing through a systematic domain-based classification. We also review different pilot projects on P2P sharing across the globe. Finally, we identify and discuss a number of challenges that need to be addressed for scaling up P2P sharing in the electricity market followed by concluding remarks at the end of the paper.

Tushar, Wayes↗
DOE OSTI2024

Deep Generative Models in Energy System Applications: Review, Challenges, and Future Directions

In recent years, with the advent of mature machine learning products like ChatGPT, Stable Diffusion, and Sora, the world has witnessed tremendous changes driven by the rapid development of generative artificial intelligence (GAI). Beyond applications in text, speech, image, and video creation, deep generative models (DGMs) underpinning these cutting-edge technologies have also been employed by domain researchers to address scientific and engineering challenges. This paper aims to fill a gap in the research community by providing a systematic review of how DGMs have been utilized in energy system applications. After introducing four most popular DGMs, we review and categorize 196 research articles into five focus areas: data generation, forecasting, situational awareness, modeling, and optimal decision-making. Through this classification, we uncover trends in how DGMs are employed for each type of problem, highlighting GAI techniques that contribute to breakthroughs over traditional methods. We discuss limitations in existing literature, engineering challenges, and propose future directions, all tailored to the unique nature of problems in energy system engineering. Our goal is to offer insights for energy system domain researchers, providing a comprehensive view of existing studies and potential future opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Inertia estimation for power grids: A review of methods, challenges, and future prospects

The electric power grid is undergoing a significant transformation, shifting from traditional synchronous generators to inverter-based resources (IBRs) such as solar photovoltaics, wind turbines, and energy storage systems. This evolution leads to a reduction in system inertia, a critical attribute for maintaining frequency stability in response to disturbances. Consequently, the ability to monitor and estimate system inertia has become increasingly essential. This paper provides a comprehensive review of existing inertia estimation methodologies, analyzing them from multiple perspectives, including the types of data utilized, underlying estimation principles, operational modes, and system-wide applicability. A comparative summary table is included to distill commonalities and key characteristics across various studies. In addition, the paper examines practical implementations of inertia estimation across several major power systems worldwide, including the U.S. interconnections, the Nordic power system, and the U.K. grid. Key challenges are identified, particularly in estimating contributions from virtual inertia sources and load-induced inertia in increasingly converter-dominated networks. To address these emerging challenges, the paper proposes an integrated framework for real-time inertia estimation and monitoring. This framework encompasses critical components such as data acquisition, inertia estimation from both synchronous and non-synchronous sources, load-induced effects, optimization techniques, forecasting, and virtual inertia scheduling. Collectively, these elements enable dynamic, system-wide monitoring and adaptive control of grid inertia.

Inertia estimation↗
DOE OSTI2021

Opportunities and challenges for flow-through hydrothermal pretreatment in advanced biorefineries

Hydrothermal pretreatment (HTP) using only water offers great potential to reduce the overall cost of the bioconversion process. However, traditional HTP performed in a batch has limitations in removing lignin and often needs to be performed under severe conditions to achieve reasonable pretreatment effects. Additionally, lignin left in the pretreated residue at these conditions is also highly condensed, thus possessing an even more adverse impact on the hydrolysis process, which requires high enzyme loadings. To address these technical challenges, HTP performed in a flow-through configuration was developed to simultaneously achieve near-complete hemicellulose recovery, high lignin removal and high sugar release. Despite facing challenges such as potentially large water usage, flow-through HTP still represents one of the most cost-effective and eco-friendly pretreatment methods. This review mainly covers the latest cutting-edge innovations of flow-through HTP along with structural and compositional changes of cellulose, hemicellulose, and lignin before and after pretreatment.

09 BIOMASS FUELS↗
DOE OSTI2025

Review of the potential and challenges of MOF-based adsorption heat pumps for sustainable cooling and heating in the buildings

Heat pumps are regarded as the most suitable means to meet the future demand of heating and cooling in the building, as they require small input of electrical energy and output high thermal energy. Vapor compression heat pump (VCHP) and transcritical-CO 2 heat pump are the two major heat pump technologies currently dominating the market. However, VCHP system suffers from its fugitive emission of hydrofluorocarbon (HFC) refrigerants, and transcritical-CO 2 system requires high operating pressure (typically 9–13 MPa). For low-to-medium temperature heating and cooling applications thermally driven adsorption heat pump (AHP) provides a better alternative to VCHP and transcritical-CO 2 system as AHP uses natural refrigerants and operates at a much lower pressure. But currently available AHP technology has the limitation of low coefficient of performance (COP). Advances in synthesizing metal-organic frameworks (MOF) with high gas adsorption capacity have created an opportunity to address the problem of low COP of current AHP technology. Here, this article reviews the progress made in the past decade in utilizing MOF and conventional adsorbents with different working fluids in AHP technology and compares their performance. The article also summarizes the key challenges for the MOF-based AHP technology and provides the authors’ perspective to address these challenges.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Extreme events, energy security and equality through micro- and macro-levels: Concepts, challenges and methods

Low-income households face long-standing challenges of energy insecurity and inequality (EII). During extreme events (e.g., disasters and pandemics) these challenges are especially severe for vulnerable populations reliant on energy for health, education, and well-being. However, many EII studies rarely incorporate the micro- and macro-perspectives of resilience and reliability of energy and internet infrastructure and social-psychological factors. To remedy this gap, we first address the impacts of extreme events on EII among vulnerable populations. Second, we evaluate the driving factors of EII and how they change during disasters. Third, we situate these inequalities within broader energy systems and pinpoint the importance of equitable infrastructure systems by examining infrastructure reliability and resilience and the role of renewable technologies. Then, we consider the factors influencing energy consumption, such as energy practices, socio-psychological factors, and internet access. Finally, we propose interdisciplinary research methods to study these issues during extreme events and provide recommendations.

Chen, CF↗
DOE OSTI2024

Opportunities and challenges in cathode development for non-lithium-ion batteries

Lithium (Li)-ion batteries have stimulated the societal transformation to clean energy systems. This carry-on electricity is revolutionizing how society communicates, functions, and evolves efficiently by enabling mobile electronics, zero-emission electric vehicles, and stationary energy storage. In preparation for the sustainable energy future, however, there are growing concerns about depleting critical elements used in the Li technology (e.g., lithium, cobalt, and nickel), especially for large-scale applications that will accelerate the rate of elemental consumption. Various non-Li-based rechargeable batteries composed of earth-abundant elements, such as sodium, potassium, magnesium, and calcium, have been proposed and explored as alternative systems to promote sustainable development of energy storage. In this perspective, we discuss challenges in Li-ion batteries in the sustainability aspect and provide our opinions on the potential applications of non-Li-based batteries. We also highlight the current status, important progress, and remaining challenges of the Li-alternative technologies.

25 ENERGY STORAGE↗