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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 OSTI2023

Experiment Design and Preparation for a Shielding Benchmark Utilizing Godiva-IV

An experiment is currently being designed to provide a high-quality shielding benchmark for Criticality Accident Alarm System (CAAS) modeling. Previous benchmarks have suffered from uncertainty primarily due to two factors. The first factor is radiation that is not directly coming from the source, also known as room return. Room return is notoriously difficult to account for in experimental data and to model in benchmarks. The second factor is uncertainty associated with the source term itself. In order to reduce these two sources of uncertainty, this experiment will utilize a room return shield [1] that will reduce the effect of room return and previous work performed to ensure the reproducibility of the source term. The experiment will use the Godiva IV [2] assembly located at the National Criticality Experiments Research Center (NCERC) to provide a neutron source representative of a criticality accident. Previous experiments [3]-[4] have shown that Godiva IV is capable of producing both bursts and steady-state emissions of equal magnitude which will allow for reduced uncertainty in the source term. The room return shield will house and isolate the shielding samples, neutron activation foils, and other detectors. Data collected will provide a comparison of the neutron and gamma dose for shielded and unshielded configurations. This data will be used to validate shielding data used for modeling criticality accident alarm systems. Shielding samples included in this benchmark are C, Fe, NaCl, Pb, high density polyethylene, and SiO 2 . This paper details the design of the room return shield, the experimental plan, challenges, and mitigation strategies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Failure Mode and Effects Analysis Summary Report

This report provides an overview of the development of failure modes and effects analysis (FMEA) and its implementation as a systematic criticality and risk assessment tool supporting a quality by design (QbD) approach for FCIC research. This report also provides a high-level overview of the results for the FMEA evaluation of two feedstock preprocessing system configurations: (1) generation of pine residue materials for high-temperature pyrolysis conversion and (2) generation of corn stover materials for low-temperature conversion using deacetylation and disc mechanical refining pretreatment for fermentation to hydrocarbons. For the results presented in this report, our FMEA interviews included two approaches. The first approach was to perform FMEA interviews for the entire system of unit operations giving a wholistic system level view. The second approach consisted of detailed interviews for each individual unit operation within the system allowing for a “deep dive” into the specific failures for the individual components within the configuration. These two approaches provide different resolutions of information. The FMEA results of this report were focused on failures associated with meeting critical quality attributes (CQAs) identified for the target conversion processes for each processed feedstock type. The information gathered through the FMEA interviews include estimations of risk scores for meeting each given CQA specification, identification of the impacts for not meeting a CQA specification, capturing causes associated with material attributes and process parameters for each failure, identification of current detection methods, and speculation of potential mitigation strategies for decreasing a failure’s risk score. The complete results of all FMEA interviews are provided in the Appendices of this report.

conversion↗
DOE OSTI2023

Lifecycle Management of Nuclear Security Radiation Detection Systems: Testing and Evaluation

The lifecycle of radiation detection systems functioning within a State’s Nuclear Security Detection Architecture encompasses all activities associated with acquisition, deployment, and eventual disposal. Throughout a system’s lifecycle, testing and evaluation activities are needed to ensure requirements are continually met, as underscored by recent experiences.This paper provides:1.A discussion of reasons why testing should be part of the radiation detection equipment lifecycle before, during, and after acquisition.2.A general process for determining applicable evaluation methods.3.A discussion of issues related to integrating testing and evaluation into procurement and operational processes and mitigation strategies.

Harris, Tyrone↗
DOE OSTI2023

Defect Characterization of Monocrystalline Silicon Solar Cells with Polysilicon Passivated Contact Using Electrically-Detected Magnetic Resonance (EDMR) Spectroscopy

As the c-Si based solar cell efficiencies are approaching over 26%, it is becoming critical to characterize the low concentrations of the defects – as low as 10^10-10^11 cm-3 (for e.g., iron contamination in high-lifetime Ga-doped wafers3 and n-type wafers), and further reduce them. Also, atomistic level understanding of the mechanisms of the low concentration process-induced-defects and reliability limiting defects (such as light and elevated temperature induced degradation, surface passivation degradation) is needed to design the mitigation strategies. The conventional characterization techniques are limited due to their detection limitations. Some of the techniques based on lifetime spectroscopies can still be used for low concentration characterization however, they are based on estimations and theoretical models and hence, indirect and cannot fully reveal information about the microscopic mechanism of the defects. Thus, we present the application of an ultrasensitive magnetic resonance-based technique for the direct spectroscopic detection of the defects in Si PV - electrically detected magnetic resonance (EDMR). In this work, we aim to focus on establishing a process flow for fabrication of minicells with (miniature replica of the larger-area cells) and setting up the routine for EDMR measurements on them with the EDMR instrumentation capability at NREL. For the EDMR measurements, sample size is limited by the dimensions of sample holder tube (width less than 3.2 mm, active area - 20 mm). Thus, we have designed c-Si based minicells with polysilicon (poly-Si) passivated contacts same as the larger-area cells that we fabricate in our group at NREL. We also modified our minicell process flow for fabricating the textured minicells for preserving the texture during processing and taking care of the laser-ablation edge damage which can significantly affect the performance of such small devices. We have achieved comparable performance on these newly fabricated minicells as that of our 4 cm2 devices with same structure (comparable VOC, JSC, FF). We also conducted EDMR measurements on the minicells and observed a distinct EDMR signal at g-value ~2.005 at temperatures 30K and above, as shown in Fig. 2. We associate this signal to the presence of silicon dangling bonds based on the g-value. We also observed an EDMR signal at g-value ~1.998 at temperature ~5K. The origin of this signal is still being investigated. Thus, we show the proof of concept of minicells and EDMR measurements with which we now aim to study some of the unknown defects in silicon solar cell devices.

EDMR↗
DOE OSTI2023

Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities

Although deep learning has made great progress in recent years, the exploding economic and environmental costs of training neural networks are becoming unsustainable. To address this problem, there has been a great deal of research on algorithmically-efficient deep learning, which seeks to reduce training costs not at the hardware or implementation level, but through changes in the semantics of the training program. In this paper, we present a structured and comprehensive overview of the research in this field. First, we formalize the algorithmic speedup problem, then we use fundamental building blocks of algorithmically efficient training to develop a taxonomy. Our taxonomy highlights commonalities of seemingly disparate methods and reveals current research gaps. Next, we present evaluation best practices to enable comprehensive, fair, and reliable comparisons of speedup techniques. To further aid research and applications, we discuss common bottlenecks in the training pipeline (illustrated via experiments) and offer taxonomic mitigation strategies for them. Finally, we highlight some unsolved research challenges and present promising future directions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Failure Modes and Effects Analysis of Biorefinery Pathways

This talk provides an overview of failure modes and effects analysis (FMEA) development and implementation as a systematic criticality and risk assessment tool for biorefinery pathways within the FCIC. This supports a quality by design (QbD) approach, and this talk provides a high-level overview of the results for the FMEA evaluation focused on the generation of pine residue materials for high-temperature pyrolysis conversion. the FMEA interviews included two approaches. The first approach was based around the entire system of unit operations giving a wholistic system level view. The second approach used detailed interviews from individual unit operation within the system allowing for specific failures for individual system components. These two approaches provide different resolutions of information about the reliability and risk. The FMEA results focused on failures associated with meeting critical quality attributes (CQAs) identified for the high temperature conversion of loblolly pine residues and were supplemented with experimental data supporting process upsets and reliability also collected within the consortium. Estimations of risk scores for meeting each given CQA specification, identification of the impacts for not meeting a CQA specification, capturing causes associated with material attributes and process parameters for each failure, identification of current detection methods, and speculation of potential mitigation strategies for decreasing a failure’s risk score were gathered through the FMEA interviews, and were combined to understand the overall process risk metrics and where technology, process, and knowledge improvements are needed in order to de-risk emerging biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2013

Architectural Framework for Addressing Legacy Waste from the Cold War - 13611

We present an architectural framework for the use of a hybrid simulation model of enterprise-wide operations used to develop system-level insight into the U.S. Department of Energy's (DOE) environmental cleanup of legacy nuclear waste at the Savannah River Site. We use this framework for quickly exploring policy and architectural options, analyzing plans, addressing management challenges and developing mitigation strategies for DOE Office of Environmental Management (EM). The socio-technical complexity of EM's mission compels the use of a qualitative approach to complement a more a quantitative discrete event modeling effort. We use this model-based analysis to pinpoint pressure and leverage points and develop a shared conceptual understanding of the problem space and platform for communication among stakeholders across the enterprise in a timely manner. This approach affords the opportunity to discuss problems using a unified conceptual perspective and is also general enough that it applies to a broad range of capital investment/production operations problems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Neutron-Gamma flux and Dose calculations in a Pressurized Water Reactor (PWR)

The Institute of Radiological Protection and Nuclear Safety (IRSN) acts as technical support to the French nuclear safety authorities. In this context, one of its missions is to improve nuclear safety through the enhancement of knowledge regarding operating nuclear power reactors. The issues concerning the aging and the characterisation of the reactor vessel require knowledge of the neutron and gamma radiation environment on the vessel and beyond. Since few years, ENEA (Energia Nucleare e Energie Alternative, i.e. Nuclear Energy and Alternative Energy agency) and IRSN collaborate on Monte-Carlo simulations and Variance Reduction Techniques (VRT), which are used to determine neutron and gamma spectra in and out of the core. Additionally, IRSN participates in the DISCOMS project, which stands for 'Distributed Sensing for Corium Monitoring and Safety', aiming at examining the status of the third barrier of confinement, in order to define possible mitigation strategies in case of a severe accident, namely: i) reactor pressure vessel breakthrough and corium relocation outside the vessel, ii) reactor pit concrete erosion and iii) corium cooling. One of the IRSN tasks in the frame of the DISCOMS project is to provide the radiation level in terms of neutron and gamma doses and flux energy spectra at various locations. This paper summarizes the study performed on the radiation transport in the Tihange-I Belgian nuclear reactor and contributes to several issues requiring the knowledge of the radiation environment in and outside the reactor vessel. This paper gives an overview of the work presented at the ICRS-13 and RPSD-2016 conference (for more details see the proceedings paper)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Neutron production in lunar habitats - Paper 132

Lunar habitats constructed of either local materials or conventional materials used for spacecraft (such as aluminum) will provide protection for astronauts from solar energetic particles (SEP) and galactic cosmic rays (GCR). Although there are essentially no neutrons in the primary GCR and SEP fields, neutrons are produced by interactions of those fields with the lunar surface and with the lunar habitat. In a habitat, the neutrons can be divided into two categories: albedo neutrons moving generally upward through the habitat, and a generally downward flux created by interactions in the habitat walls. These two neutron fields differ in their energy spectrum, and as a result different mitigation strategies may be needed for different areas of the habitat in order to reduce the dose from neutrons. In this work, we calculate the 'upward' and 'downward' neutron fluences, using a variety of shielding materials and thicknesses. We also investigate the effect of other materials inside the habitat on the neutron fluences. The preliminary transport model calculations performed here verify the effectiveness of a hydrogenous shielding wall material, polyethylene, in reducing the neutron dose inside a simple lunar habitat geometry when compared to walls made of lunar regolith and aluminum. Separate transport model calculations were done for the albedo neutron spectrum rising up from the lunar soil and for GCR particles incident upon the habitat shielding. In the case of GCR ions incident on the habitat, shielding wall made of polyethylene reduced the neutron effective dose by a factor of three, compared to the other two shielding materials. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2024

Cybersecurity Considerations for Emerging Energy Technologies

AI, cloud computing, post-quantum cryptography, zero-trust architectures, microgrids, and virtual power plants. What do these things have in common? They are all emerging technologies in the clean energy space that will be a critical part of grid modernization efforts. As we work towards clean energy and decarbonization targets, these technologies, developed to solve real-world problems, will help us reach goals and achieve new efficiencies as the paradigm of grid operation shifts. However, there are growing concerns about the cybersecurity risks associated with these trending topics as they are used in critical infrastructure applications. This talk will cover gaps, challenges, and opportunities for the secure implementation of grid modernization solutions and novel energy applications of state-of-the-art networking and communications. Proactive risk mitigation strategies, including the application of cyber-informed engineering, will be discussed. Practical applications of these techniques will help provide countermeasures to the impact of cyberattacks on critical infrastructure technologies in a new, digitized grid landscape.

14 SOLAR ENERGY↗
DOE OSTI2024

Beyond Binary: Automated PLC Memory Forensics through RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and the evolution of industrial control systems (ICS) to adopt Internet-based technologies enhanced productivity, but have inadvertently increased their vulnerability to cyber-based malicious attacks. When an ICS system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies to safeguard against future instances. Memory forensics is critical in the analysis process to ascertain what occurred. To date, approaches to analyze the persistent memory in ICS devices are limited, and almost nonexistent for volatile memory. This paper proposes an automated methodology, COMA, for PLC memory dump analysis using computer vision and deep learning techniques. Specifically, COMA converts the sequences of bytes in a PLC memory dump to RGB pixels and creates a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. COMA then uses the trained model to automatically segment new memory images and extract forensic artifacts. We evaluate COMA on a Schneider Electric Modicon M221 PLC involving two cyber-based attack scenarios: (i) code injection and (ii) code modification. The empirical results show that COMA can successfully detect attack artifacts in memory dumps in both scenarios.

Asmar Awad, Rima↗
DOE OSTI2024

Growth of Native Oxides of Niobium Thin Films for Superconducting Qubits with Etching Chemistry

Niobium thin films have been broadly applied in building superconducting qubits for quantum computing hardware. While improvements have been made by device engineering efforts, scaling the energy-sensitive quantum system requires materials study for further improvements. In this study, we performed XPS and ToF-SIMS analysis for Nb thin films across samples with different manufacturing techniques. By varying the air exposure time of the samples, this research comparatively investigates the chemical and depth profile of native oxides before and after the etching process. We observe a rapid logarithmic growth of oxide thickness across all samples and the dominant presence and growth of Niobium pentoxide in atomic percentage concentration on the surface. This comparative study provides insight into oxides mitigation strategies and correlation with qubits performance.

Lei, Zhicheng↗
DOE OSTI2024

Comparing Interaction Graphs on Cascading Outages under Different Loading Conditions

Interaction graphs on cascading outages of power systems provide valuable insights into how cascading outages evolve and propagate, and which components and links are critical to the propagation of cascading outages, enabling further development of mitigation strategies to support decision-making. However, the sensitivity of the interaction graph’s topology to the system’s loading condition has not been studied sufficiently. This paper compared interaction graphs under various loading conditions on the Northeastern Power Coordinating Council 140-bus system, and discovers the strong relationships between the graph topology, the cascade size distribution, and the load condition. Accordingly, three representative interaction graphs are constructed and illustrated.

Guo, Zhenping↗
DOE OSTI2024

Decision Points and Practical Considerations for AI Projects

In this presentation, I will present business-relevant decisions, risks, and considerations for practical implementations of AI projects. I will use energy efficiency and renewable energy AI projects at NREL as examples and case-studies highlighting the journey from concept to implementation. First, I present challenges, questions, and trade-offs related to system inputs: the data. Next, I will examine issues with system behavior and trust, presenting examples, risks, and mitigation strategies. Finally, I will discuss challenges to effective widespread deployment of AI systems including energy, compute, and time requirements.

AI↗
DOE OSTI2025

Optimization of the light detection system of the ICARUS detector

The Short Baseline Neutrino (SBN) Program at Fermilab is designed to investigate short-baseline neutrino oscillations and test the hypothesis of sterile neutrinos, motivated by several experimental anomalies observed over the past decades. Within this program, the ICARUS experiment plays a key role. It employs the world’s largest Liquid Argon Time Projection Chamber (LArTPC) and serves as the farthest and most sensitive SBN detector for studying muon and electron neutrino oscillations. A crucial subsystem of the ICARUS detector is the Light Detection System (LDS), which captures the prompt scintillation light produced by neutrino interactions in the 600-ton active liquid Argon volume. This system provides precise timing information that is essential for event reconstruction, the trigger system, and cosmic background rejection. The LDS is composed of 360 Hamamatsu R5912-MOD 8-inch photomultiplier tubes (PMTs), operating under cryogenic conditions ($\sim 87 \ K$) inside the detector’s cryostats. During the detector’s operation at FNAL, a degradation in PMT gain has been observed, attributed to aging under low-temperature conditions. In collaboration with ICARUS teams from INFN Pavia and Catania, I developed an experimental setup to study the temperature-dependent behavior of the PMTs, performing gain measurements both at room temperature and down to $-70°C$ using a climatic chamber at INFN Catania. The results indicate that while the PMTs maintain stable gain at room temperature, a significant and permanent gain reduction occurs at low temperatures. Although $-70°C$ is still warmer than liquid Argon temperatures, the findings clearly demonstrate a gain-dependent performance degradation. The thesis also discusses mitigation strategies implemented in the ICARUS detector to address this issue and presents a simplified model to describe and simulate the observed behavior.

Saia, Clara [Catania U.] (ORCID:0009000464102417)↗
DOE OSTI2024

Recovery of Natural Gas Equipment Emissions into Gas Compression Engines for the Reduction of Potential Greenhouse Gas Emissions

Since the turn of the millennium, the United States (U.S.) oil and natural gas (ONG) industry has nearly doubled its natural gas production rate. As a result, the ONG industry has recently come under increasing scrutiny for its contributions to greenhouse gas (GHG) emissions. Consequently, various solutions to this problem have been proposed and formulated to reduce the impacts of GHG emissions on the environment. West Virginia University (WVU) have found it important to research the impacts of recovering vented gas streams into prime-mover engines. The U.S. Department of Energy (DOE) and National Energy Technology Laboratory (NETL) have granted WVU funding to research and develop a “Methane Mitigator” (M2) - a “Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry.” One of the main areas of interest for this research was the collection of emissions from natural gas equipment into a Caterpillar G3508J natural gas compression engine. The parameters being analyzed from the engine were brake-specific emissions and power output. The emissions sources considered for this research were pneumatic controllers (PCs), reciprocating compressor vents, and the engine’s open crankcase breather. The compressor vent and PC emissions were simulated using a mass flow controller (MFC) and flowed into the engine using two separate methods: (1) directly into the air intake, and (2) through a retrofitted closed crankcase ventilation system (CCV), serving as a buffer volume. The crankcase emissions were quantified without the CCV, and the impact on exhaust emissions from circulating the crankcase gases into the intake was measured. The simulated compressor vent and PC flows from the MFC had limited effect on the steady state operation of the engine and resulting performance. When the simulated flows were fed directly into the engine’s air intake, the changes within the engine’s continuous performance and emission parameters were larger but lasted for shorter durations. Conversely, when the simulated flows were fed into the CCV before entering the air intake, the changes in the engine’s performance and emission parameters were less pronounced for continuous analysis but lasted for longer durations. In either case, the continuous emission changes in both emissions and performance varied in size depending on the test scenario being run, but the cycle average changes in emissions and performance showed little impact overall compared to the engine’s baseline operation. As a result, the inclusion of a CCV shows a decrease in baseline carbon dioxide equivalent (CO2-eq.) engine emissions (from combined exhaust and open crankcase) of almost 4%. Likewise, the CCV inclusion reduced baseline total methane (CH4) from combined exhaust and open crankcase by upwards of 16%. These atmospheric emissions only decreased further with the inclusions of collected PC and compressor vent flows. The resulting changes in time-averaged rated exhaust behavior (or lack thereof) prove that the proposed M2 system could likely be deployed at sites with modern lean-burn natural gas engines as a viable option for reducing and eliminating potential GHG sources that would have otherwise been unutilized as energy sources.

03 NATURAL GAS↗
DOE OSTI2025

Development of mechanistic, microstructure-informed BISON models for fission product-induced failure mechanisms in advanced nuclear fuels

The US continues to prioritize commercial deployment of advanced reactors—particularly those utilizing U-Zr metallic and TRISO particle fuels. Fission product-induced failure mechanisms for these systems include fuel–cladding chemical interaction in metallic fuel rods, which threatens cladding integrity, and Pd penetration in TRISO particles, which degrades SiC layer properties. Empirical models can be applied within the bounds of existing irradiation databases, but their utility is limited when considering new designs or investigating fundamental material behaviors. The Nuclear Energy Advanced Modeling and Simulation Program is therefore developing mechanistic models for these behaviors, which are expected to aid in fuel design, assist in development of failure mitigation strategies, and provide support for qualification and licensing. These efforts leverage multiscale capabilities to capture the microstructural features and processes that govern these behaviors. This talk summarizes past and ongoing efforts to develop and validate these models for the BISON fuel performance code.

FCCI↗
DOE OSTI2026

Low-Energy Radon Backgrounds from Electrode Grids in Dual-Phase Xenon TPCs

The dual-phase xenon time projection chamber (TPC) is a powerful technology to detect rare interactions such as scatters of dark matter particles on nuclei. In particular, the built-in gain of ionization signals in a dual-phase TPC makes it sensitive to events in the few-electron regime, as expected from low-mass dark matter interactions. The pursuit of this low-energy sensitivity through ionization-only signal detection has so far been hindered by excessive electron backgrounds observed across experiments. Much of this background is attributed to the plate-out of $^{222}$Rn decay chain isotopes on the high voltage electrode grid surfaces that span the full cross section of the TPC. This work presents a first-principle model constructed for this background, the predictions of which are consistent with data from the LZ and LUX experiments. We then discuss mitigation strategies of this background in future dual-phase TPCs and the possibility of applying this grid background model to ionization-only dark matter searches.

Akerib, D. S. [SLAC; KIPAC, Menlo Park]↗