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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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DOE OSTI2025

Mechanical and Thermal Characterization of Additively Manufactured Carbon/Nylon 12 and Carbon/PEEK Composites

This study explores additive manufacturing of carbon fiber-reinforced thermoplastic composites using the Composite-Based Additive Manufacturing (CBAM) process. Carbon/Nylon 12 and Carbon/PEEK composites were fabricated and evaluated through mechanical (compression, tensile, flexural, and impact) and thermal (DSC and TGA) tests. Carbon/PEEK exhibited superior mechanical performance, with 97.5% higher tensile strength, 79.8% higher elastic modulus, and 59.6% higher flexural strength compared to Carbon/Nylon 12. Thermal testing showed that Carbon/PEEK had higher thermal stability, beginning degradation at 350 °C versus 298 °C for Carbon/Nylon. These results indicate that CBAM-fabricated Carbon/PEEK composites are suitable for applications requiring high strength and temperature resistance.

Additive manufacturing↗
DOE OSTI2022

Peer-to-Peer Energy Trading under Network Constraints Based on Generalized Fast Dual Ascent

We report the wide deployment of renewable energy resources, combined with a more proactive demand-side management, is inducing a new paradigm in both power system operation and electricity market trading, which especially boosts the emergence of the peer-to-peer (P2P) market. A more flexible local market mechanism is highly desirable in response to fast changes in renewable power generation at the distribution network level. Moreover, large-scale implementation of P2P energy trading inevitably affects the secure and economic operation of the distribution network. This paper presents a new P2P electricity trading framework with distribution network security constraints considered using the generalized fast dual ascent method. First, an event-driven local P2P market framework is presented to facilitate short-term or immediate local energy transactions. Then, the sensitivity analysis of nodal voltage and network loss with respect to nodal power injections is used to evaluate the impacts of P2P transactions on the distribution network, which ensures the secure operation of the distribution system. Thereby, the external operational constraints are internalized, and the cost of P2P energy trading can be appropriately allocated in an endogenous way. Moreover, a generalized fast dual ascent method is employed to implement distributed market-clearing efficiently. Finally, numerical results indicate that the proposed model could guarantee secure operation of the distribution system with P2P energy trading, and the solution method enjoys good convergence performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

A Scalable HPC Insider Threat Monitoring System

Cyber Equations, Inc. is reporting on the results of its DOE SBIR Phase I project for the development of a Scalable HPC Insider Threat Monitoring System. This final report to the Department of Energy for Task DE-FOA-0001618 covers the period from 02/21/2017 to 02/20/2018 and summarizes the larger research accomplishments, which can be divided in theoretical and laboratory experiments. One of the many challenges for the U.S. Department of Energy (DOE) is the support of the high-performance computing (HPC) centers while providing quality information services, strategic vision, leadership, technical expertise, and capabilities necessary to enable the DOE to deliver effective, efficient, economical, and secure HPC services. In order to realize a secure DOE laboratory enterprise, DOE facilities operations must counter a wide range of cyber insider threats, from unsophisticated adversaries up to advanced, nation state sponsored actors. The DOE laboratories also presents an enormous insider attack surface of an ever-growing number of computers, networks, and devices all running a myriad of software. In addition, the DOE laboratories are connected to a variety of external organizations which multiplies the possibility of insider threat. During this SBIR project Cyber Equations developed a strategic combination of supervised and unsupervised machine learning techniques to control scale and classify whether entities, such as hosts, actors, or documents, are showing suspicious insider behavior. We conducted experiments using real cyber data to show that changes in observable behavior (e.g., changes in outbound traffic patterns) are indicative of attacks executing (e.g., insiders exfiltrating data, bots calling home, or an attack spreading). The features and methods we use, have been used in the anomaly detection research and development community for a significant amount of time and robust implementations are openly available. K-Means clustering, Decision Trees, and Support Vector Machine based classifiers are readily available through the R language and open source H20 machine learning framework. The Cyber Equations approach is novel in its use of these classifiers combined with Hadoop based parallel processing technology. The five stages of processing used by CyberInsider improve scalability and reduce the high number of false positives normally associated with network anomaly detection. In summary, the Cyber Equations has successfully accomplished all of its Phase I tasks and demonstrated the feasibility of the Insider Threat Monitoring System.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Impact of Emergency Diesel Generator Reliability on Microgrids and Building-Tied Systems

Microgrids are an emerging alternative as an energy backup system for critical electric loads and have improved performance compared to the traditional architecture where a single emergency diesel generator is tied to an individual building. Both architectures are dependent on the reliability of their individual generators and a quantitative and realistic comparison of the overall system reliability of the two architectures is lacking. Using recently published work on emergency diesel generator finite reliability, a quantitative methodology is presented to compare the reliability of a microgrid architecture based on centralized emergency diesel generators to the traditional approach of generators tied to individual buildings. Three system reliability performance metrics are calculated as a function of outage duration: (1) probability to meet 100% of the critical load; (2) expected fraction of lost load; and (3) probability to meet the highest priority critical loads. It is shown that stand-alone building-tied emergency diesel generators systems, even when two emergency diesel generators are used per building, cannot provide the reliability required to sustain critical loads for a grid outage lasting multiple days. Due to their network configuration and ability to share load, diesel generator-based microgrid configurations are estimated to have = 93% probability of powering all buildings for a 2-week outage there the individual building-tied emergency diesel generator architecture has a =20% probability. Microgrids do present other susceptibilities that are site specific and should be considered including vulnerabilities associated with the on-campus distribution system and cybersecurity.

backup power↗
DOE OSTI2025

Natural Hazard Forecast Alert Grid Risk System

Weather events cause most power outages. Often, we even get notifications on our phones to take cover or be prepared for an imminent event. If electric grid utilities had a similar warning that also included probable scenarios and the equipment involved, they could prepare and minimize the effects. Idaho National Laboratory had a project with the U.S. Department of Energy’s Cybersecurity, Energy Security, and Emergency Response program to develop a grid alert application that receives messages from the existing emergency alert system, filters and determines components possibly affected by the emergency event, calculates probable scenarios using MASTERRI (Modeling And Simulation for Targeted Reliability and Resilience Improvement). For high-risk events, the application can then send alert links to subscribed electric distribution utility operations staff to allow them to see and evaluate the scenarios and the impact in a web based interactive map tool. This proof of concept application used data from utilities and organizations, such as the international regulatory body North American Electric Reliability Corporation, which have complied historical failure data of elements that comprise the U.S. electric grid. Nominal failure rates are obtained from this data. To make this tool possible, estimated failure rates were calculated for different component types given the alert type, severity, and location. Historic weather-related grid element failures were correlated with historic weather events from the Integrated Public Alert & Warning System. These correlated events and failures are used along with Bayesian updates from the historical norms to provide a modified failure rate for grid elements in the alert areas and calculate probable scenarios. Working with an industry collaborator, actual grid models and data were used for demonstration cases. This report outlines the work performed for this project.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

IDENTIFYING ELUSIVE ELECTROMAGNETIC COUNTERPARTS TO GRAVITATIONAL WAVE MERGERS: AN END-TO-END SIMULATION

Combined gravitational wave (GW) and electromagnetic (EM) observations of compact binary mergers should enable detailed studies of astrophysical processes in the strong-field gravity regime. This decade, ground-based GW interferometers promise to routinely detect compact binary mergers. Unfortunately, networks of GW interferometers have poor angular resolution on the sky and their EM signatures are predicted to be faint. Therefore, a challenging goal will be to unambiguously pinpoint the EM counterparts of GW mergers. We perform the first comprehensive end-to-end simulation that focuses on: (1) GW sky localization, distance measures, and volume errors with two compact binary populations and four different GW networks; (2) subsequent EM detectability by a slew of multiwavelength telescopes; and (3) final identification of the merger counterpart amidst a sea of possible astrophysical false positives. First, we find that double neutron star binary mergers can be detected out to a maximum distance of 400 Mpc (or 750 Mpc) by three (or five) detector GW networks, respectively. Neutron-star-black-hole binary mergers can be detected a factor of 1.5 further out; their median to maximum sky localizations are 50-170 deg{sup 2} (or 6-65 deg{sup 2}) for a three (or five) detector GW network. Second, by optimizing depth, cadence, and sky area, we quantify relative fractions of optical counterparts that are detectable by a suite of different aperture-size telescopes across the globe. Third, we present five case studies to illustrate the diversity of scenarios in secure identification of the EM counterpart. We discuss the case of a typical binary, neither beamed nor nearby, and the challenges associated with identifying an EM counterpart at both low and high Galactic latitudes. For the first time, we demonstrate how construction of low-latency GW volumes in conjunction with local universe galaxy catalogs can help solve the problem of false positives. We conclude with strategies that would best prepare us for successfully identifying the elusive EM counterpart of a GW merger.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Development of Upscaling Techniques and Construction of Calibrated Models for Fractured Rocks Using Discrete Fracture Network Approaches

The Pahute Mesa Corrective Action Unit on the Nevada National Security Site (NNSS) contains several fractured aquifers that can potentially provide high-permeability pathways for radionuclides to migrate away from underground nuclear testing locations. Although the geometric properties of fractures, such as length and orientation, can be found using geophysical methods and borehole image analyses, the hydraulic property of fractures (which are primarily influenced by apertures) are often unknown or have a high degree of uncertainty attached to their values. The aperture values have a profound impact on groundwater velocity and are critical to understanding transport scales at Pahute Mesa. Fracture aperture values and their distributions also have dominant control over radionuclide transport with potential for long-range correlations or scale-invariant dynamics. Understanding of the small-scale transport variability in fractures could lead to identification of distinct characteristics on larger scales. Furthermore, upscaling techniques need to be developed to adequately predict transport behavior at field scales by capturing the transport trends of smaller scale networks. This report explores these vital modeling needs to understand the role of fractures in Pahute Mesa. Discrete fracture network (DFN) models are the basis for constructing a well-calibrated model to ascertain aperture values of fractures in lava-flow aquifers. These models are also used to develop and compare the usefulness of several random-walk-based models to perform transport upscaling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Uranium from Seawater Cost Analysis: Recent Updates

While it is not meant to be a direct competitor with conventionally mined uranium, seawater uranium has significant potential to sway policy makers and the public toward the long term viability of nuclear power. Given the large mass of uranium contained within the ocean and its continual replenishment by freshwater run-off and the ocean floor, seawater uranium can be considered for all practical purposes a renewable resource. In addition to this assurance of supply security placing nuclear power on equal footing with other renewable energy generation technologies, seawater uranium removes a key uncertainty by establishing a cost ceiling on uranium based fuels. Given the evolving nature of this technology, this paper aims to provide an update of the economic model to reflect recent progress. This analysis will reference a passive collection system currently under development by Oak Ridge and Pacific Northwest National Labs. This system consists of a polymer modified to contain amidoxime functional groups, a ligand with high uranium affinity. The adsorbing material is then braided into long segments so it may be moored to the bottom of the ocean where it passively collects uranium for a period on the order of weeks to months. Upon completion of its soaking campaign adsorbent is winched to the surface by work boats so the uranium may be eluted off the braids. After a chemical rinse the braids may then be redeployed for another soaking campaign and uranium elution. The adsorbent can be redeployed as many times as is economically feasible, which is a function of the degradation the material suffers upon each reuse. Noteworthy experimental progress has tightened the gap separating estimates of the optimistic and pessimistic case uranium production cost relative to the most recent analysis. It has been demonstrated before that significant uncertainty in adsorbent performance, and thus recovery cost, arises primarily from variability in adsorbent degradation upon reuse and the effects of marine biofouling on uptake. While the underlying recovery mechanism remains, significant changes have been made regarding the method of adsorbent synthesis, propagating to improvements in adsorbent durability. Additionally, further experimentation regarding the area of marine biofouling has tightened the range of expected adsorbent performance when placed in true marine conditions.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2012

NMIS with Imaging and Gamma Ray Spectrometry for Pu, HEU, HE and Other Materials

The Nuclear Material Identification System (NMIS) has been under development at ORNL and the National Nuclear Security Administration (NNSA) Y-12 National Security Complex since 1984. In the mid-1990s, what is now the US Department of Energy (DOE) Office of Nuclear Verification (ONV) realized that it was a useful technology for future arms control treaty applications and supported further development of the system. In 2004, fast-neutron imaging was incorporated into the system. In 2007, the ONV decided to develop a fieldable version of the system, designated as FNMIS, for potential use in future treaties. The FNMIS is being developed to be compatible with the eventual incorporation of gamma-ray spectrometry and an information barrier. This report addresses how and what attributes could be determined by the FNMIS system with gamma-ray spectrometry. The NMIS is a time-dependent coincidence system that incorporates tomographic imaging (including mapping of the fission sites) and gamma-ray spectrometry. It utilizes a small, lightweight (30 lb), portable deuterium-tritium (DT) neutron (14.1 MeV) generator (4 x 10 7 neutrons/second) for active interrogation and can also perform passive interrogation. A high-purity germanium (HPGe) gamma-ray detector with multichannel analysis can be utilized in conjunction with the source for active interrogation or passively. The system uses proton recoil scintillators: 32 small 2.5 x 2.5 x 10.2-cm-thick plastic scintillators for imaging and at least two 2 x 2 arrays of 27 x 27 x 10-cm-thick plastic scintillators that detect induced fission radiation. The DT generator contains an alpha detector that time and directionally tags a fan beam of some of the neutrons emitted and subdivides it into pixels. A fast (1 GHz) time correlation processor measures the time-dependent coincidence among all detectors in the system. A computer-controlled scanner moves the small detectors and the source appropriately for scanning a target object for imaging. The system is based on detection of transmitted 14.1 MeV neutrons, fission neutrons, and gamma rays from spontaneous, inherent source fission of the target, fission neutrons and gamma rays induced by the external DT source, gamma rays from natural emissions of uranium and plutonium, and induced gamma-ray emission by the interaction of the 14.1 MeV neutrons from the DT source. The NMIS can and has been used with a time-tagged californium spontaneous fission source. It has also been used with pulsed interrogation sources such as LINACs, DT, and deuterium-deuterium (DD) sources. This system is uniquely suited for detection of shielded highly enriched uranium (HEU), plutonium, and other special nuclear materials and detection of high explosives (HE) and chemical agents. The NMIS will be adapted to utilize a trusted processor that incorporates information barrier and authentication techniques using open software and then be useful in some international applications for materials whose characteristics may be classified. The proposed information barrier version of the NMIS system would consist of detectors and cables, the red (classified side) computer system, which processes the data, and the black (unclassified side) computer, which handles the computer interface. The system could use the 'IB wrapper' concept proposed by Los Alamos National Laboratory and the software integrity (digital signatures) system proposed by Sandia. Since it is based entirely on commercially available components, the entire system, including NMIS data acquisition boards, can be built with commercial off-the-shelf components. This system is being developed into a fieldable system (FNMIS) for potential arms control treaties by the ONV. The system will be modularly constructed with the RF shielded modules connected to the processor by appropriate control and signal cable in metal conduit. The FNMIS is presently being designed for eventual incorporation of gamma-ray spectrometry and an information barrier to protect classified information. The system hardware and software can be configured to obtain the following: plutonium presence, plutonium mass, Pu-240/239 ratio, plutonium geometry, plutonium metal vs non-metallic (absence of metal), time (age) since processing for plutonium (or last purification), uranium presence, uranium mass, uranium enrichment, uranium geometry, uranium metal vs non-metallic compound (absence of metal), beryllium presence and mass, tritium and deuterium gas bottle presence, HE, and chemical weapons. A matrix of the quantities determined, the method of determination, whether active (external neutron source) or passive, and the measurement equipment involved is given in the Tables 1-4. Some of these attributes can be obtained by multiple data analysis methods. The gamma-ray spectrometry methods for HEU, plutonium, and HE have been developed by other laboratories, are well known, and will be incorporated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

An Investigation of Catastrophic Failure in Solid-State Lamps Exposed to Harsh Environment Operational Conditions

Today’s lighting technology is steadily becoming more energy efficient and less toxic to the environment since the passing of the Energy Independence and Security Act of 2007 (EISA) [1]. EISA has mandated a higher energy efficiency standard for lighting products and the phase out of the common incandescent lamp. This has led lighting manufacturers to pursue solid-state lighting (SSL) technologies for consumer lighting applications. However, two major roadblocks are hindering the transition process to SSL lamps: cost and quality. In order to cut cost, manufactures are moving towards cheaper packaging materials and a variety of package architecture construction techniques which may potentially erode the quality of the lamp and reduce its survivability in everyday applications. Typically, SSL lamps are given product lifetimes of over twenty years based off of the IES TM-21-11 lighting standard which does not include moisture effects or large operational temperatures [2]. A group of recently released off-the-shelf lamps have undergone a steady-state temperature humidity bias life test of 85°C/85%RH (85/85) to investigate the reliability in harsh environment applications. The lack of accelerated test methods for lamps to assess reliability prior to introduction into the marketplace does not exist in literature. There is a need for SSL physics based models for the assessment and prediction of a lamp’s lifetime which is being spearheaded by the DOE [3]. In order to be fully accepted in the marketplace, SSL lamps must be able to perform similarly to incandescent lamps in these environments, as well as live up to the lifetime claims of manufacturers. A lamp’s package architecture must be designed with performance factors in mind, as well as address some of the known and published package related failure mechanisms, such as carbonization of the encapsulant material, delamination, encapsulant yellowing, lens cracking, and phosphor thermal quenching [4]. Each failure mechanism produces the similar failure mode of lumen degradation predominately due to two contributing factors: high junction temperature and moisture ingress. The current state-of-the-art has focused on individual areas of the lamp, such as the LED chip, substrate material, electrical driver design and thermal management techniques. [5] – [16] Looking at the lamp as a whole is a novel approach and has not been seen before in literature. This work followed the JEDEC standard JESD22-A101C of 85/85 with a one hour interval of applied voltage followed by a one hour interval of no applied voltage [17]. This test was performed continuously for each SSL lamp until it became nonoperational, i.e. did not turn on. Periodically, photometric measurements were taken following the IES LM-79-08 standard at room temperature using an integrating sphere, a spectrometer, and lighting software. The overall health of the SSL lamps was assed using the relative luminous flux (RLF), correlated color temperature (CCT) and the color difference (Δu'v') using the Euclidean distance of the CIE 1976 color space coordinates. Finally, a Weibull analysis was completed to compare the characteristic lifetime of the SSL lamp to the actual rated lifetime. An important result from this work shows that the rated lifetime does not come close to the actual lifetime when the SSL lamps are used in a harsh humid environment which is fairly common in outdoor applications across the U.S. Also, the photometric results are presented for the entire lifetime of each SSL lamp under test.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Opportunities and challenges for structural health monitoring of radioactive waste systems and structures

Radioactive waste systems and structures (RWSS) are safety-critical facilities in need of monitoring over prolonged periods of time. Structural health monitoring (SHM) is an emerging technology that aims at monitoring the state of a structure through the use of networks of permanently mounted sensors. SHM technologies have been developed primarily within the aerospace and civil engineering communities. This paper addresses the issue of transitioning the SHM concept to the monitoring of RWSS and evaluates the opportunities and challenges associated with this process. Guided wave SHM technologies utilizing structurally-mounted piezoelectric wafer active sensors (PWAS) have a wide range of applications based on both propagating-wave and standing-wave methodologies. Hence, opportunities exist for transitioning these SHM technologies into RWSS monitoring. However, there exist certain special operational conditions specific to RWSS such as: radiation field, caustic environments, marine environments, and chemical, mechanical and thermal stressors. In order to address the high discharge of used nuclear fuel (UNF) and the limited space in the storage pools the U.S. the Department of Energy (DOE) has adopted a 'Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste' (January 2013). This strategy endorses the key principles that underpin the Blue Ribbon Commission's on America's Nuclear Future recommendations to develop a sustainable program for deploying an integrated system capable of transporting, storing, and disposing of UNF and high-level radioactive waste from civilian nuclear power generation, defense, national security, and other activities. This will require research to develop monitoring, diagnosis, and prognosis tools that can aid to establish a strong technical basis for extended storage and transportation of UNF. Monitoring of such structures is critical for assuring the safety and security of the nation's spent nuclear fuel until a national policy for closure of the nuclear fuel cycle is defined and implemented. In addition, such tools can provide invaluable and timely information for verification of the predicted mechanical performance of RWSS (e.g. concrete or steel barriers) during off-normal occurrence and accident events such as the tsunami and earthquake event that affected Fukushima Daiichi nuclear power plant. The ability to verify the conditions, health, and degradation behavior of RWSS over time by applying nondestructive testing (NDT) as well as development of nondestructive evaluation (NDE) tools for new degradation processes will become challenging. The paper discusses some of the challenges associated to verification and diagnosis for RWSS and identifies SHM technologies which are more readily available for transitioning into RWSS applications. Fundamental research objectives that should be considered for the transition of SHM technologies (e.g., radiation hardened piezoelectric materials) for RWSS applications are discussed. The paper ends with summary, conclusions, and suggestions for further work. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Attack-Resilient Weighted $\ell_{1}$ Observer with Prior Pruning

Security related questions for Cyber Physical Systems (CPS) have attracted much research attention in searching for novel methods for attack-resilient control and/or estimation. Specifically, false data injection attacks (FDIAs) have been shown to be capable of bypassing bad data detection (BDD), while arbitrarily compromising the integrity of state estimators and robust controller even with very sparse measurements corruption. Moreover, based on the inherent sparsity of pragmatic attack signals, ℓ1 -minimization scheme has been used extensively to improve the design of attack-resilient estimators. For this, the theoretical maximum for the percentage of compromised nodes that can be accommodated has been shown to be 50%. In order to guarantee correct state recoveries for larger percentage of attacked nodes, researchers have begun to incorporate prior information into the underlying resilient observer design framework. For the most pragmatic cases, this prior information is often obtained through some data-driven machine learning process. Existing results have shown strong positive correlation between the tolerated attack percentages and the precision of the prior information. In this paper, we present a pruning method to improve the precision of the prior information, given corresponding stochastic uncertainty characteristics of the underlying machine learning model. Then a weighted ℓ1 -minimization is proposed based on the pruned prior. The theoretical and simulation results show that the pruning method significantly improves the observer performance for much larger attack percentages, even when moderately accurate machine learning model used.

Resilient observer, Cyber-physical systems, prunin↗
DOE OSTI2022

Multi-Level Impacts of Extreme Climate-Related Events on Food Supply Chain: Idaho Potato's Case Study

Background: The world is experiencing frequent extreme weather events like droughts, floods, snowstorms, and shifting of seasons due to climate change. Increasing frequencies and severity of these extreme weather events threaten food security because agriculture is extremely vulnerable to climate change. Higher temperature reduces overall yields of the desirable crops but proliferates weeds and harmful pests. Current data shows that every year U.S. farmers spend more than 11 billion USD to fight weeds and this number is expected to rise in the coming years due to climate change. Due to droughts, the water required for irrigation is becoming scarcer. Since many areas are becoming climatically unusable for crop production, the amount of farmland area is shrinking rapidly. In addition, changes in precipitation patterns are causing crop failures and negatively impacting expected yields. In this study, we investigated how different extreme climate events impact different stages of a food supply chain. Approach: As a case study, we chose Idaho’s potato supply chain (SC). Idaho is the top potato producing state in the U.S. and contributes around 30% of the nation’s potato production. Using the agent-based modeling (ABM) approach, we developed a multi-echelon potato supply chain computer simulation model with six types of agents – seed producers, farmers, shippers, processors, retailers, and logistics companies. In addition to the baseline scenario, we developed two additional climate-related disruption events – drought and snowstorm. We investigated how each of these disruption events impacts different stakeholders across the supply chain in terms of revenue and some other key performance metrics such as lead time, food waste, number of delayed orders, and order fulfillment rate. Results: Extreme climate events not only impact the growers but there is also cascading ripple effects downstream of the supply chain. The methodology developed in this study could be applied to other food and agricultural SC to understand the vulnerabilities of the different links. The findings would potentially help to adopt new policies for the well-being of the overall SC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The Approach of the Environmental Consequences and Impacts during Transport of Radioactive Materials (RAM)-A Safety Case - 16420

International Atomic Energy Agency (IAEA) works, together with Member States (MS), to provide a strong, sustainable and visible global nuclear safety and security framework, protecting people and the environment from the harmful effects of ionizing radiation. In the announcement of this IAEA Conference it is underlined that 'nuclear safety and security are to a great extent scientific in nature, a regulatory body with responsibilities for nuclear facilities and other licensed activities involving radioactive material needs to have permanent access to supporting expertise'. This can be provided internally to the regulatory body or through an external entity such as a TSO in order to provide a competent and timely response to regulatory needs, and the development and maintenance of an appropriate knowledge base and associated tools and services, including training and tutoring services, are the main areas on which the conference will focus. This paper presents certain results obtained during carrying out the IAEA-Romanian Scientific Research Contract entitled: 'Romanian Contribution to the Development of Methodology for Risk Assessment and State Management of Nuclear Security Regime (Risk and Radiological Consequences)' where the author served as CSI (Chief Scientific Investigator) a part of the IAEA CRP-(Coordinated Research Project) on the: 'Development of Methodology for Risk Assessment and State Management of Nuclear Security Regime'. Also, potential risks and their possible radiological consequences to peoples and environment must not be underestimated. However, the assessment of risk must be realistic and quantified, and the requirements placed on the appropriate. The IAEA regulations for the Safe Transport of Radioactive Material, 2012 Edition, Specific Safety Requirements, SSR-6, are applicable to the national and international carriage of radioactive material by all modes of transport- by road, by rail, by air, by sea or by inland waters. The Radioactive Material to be transported must be categorized on the basis of its activity concentration, total activity, fissile characteristics (if any) and other relevant subsidiary characteristics. Packaging and package requirements are then specified on the basis of the hazard of the contents and range from normal commercial packaging (for low hazard contents) to strict design and performance requirements (for higher hazard contents). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Combining Tensor Decompositions and Graph Analytics to Provide Cyber Situational Awareness at HPC Scale

This paper describes MADHAT (Multidimensional Anomaly Detection fusing HPC, Analytics, and Tensors), an integrated workflow that demonstrates the applicability of HPC resources to the problem of maintaining cyber situational awareness. MADHAT combines two high-performance packages: ENSIGN for large-scale sparse tensor decompositions and HAGGLE for graph analytics. Tensor decompositions isolate coherent patterns of network behavior in ways that common clustering methods based on distance metrics cannot. Parallelized graph analysis then uses directed queries on a representation that combines the elements of identified patterns with other available information (such as additional log fields, domain knowledge, network topology, whitelists and blacklists, prior feedback, and published alerts) to confirm or reject a threat hypothesis, collect context, and raise alerts. MADHAT was developed using the collaborative HPC Architecture for Cyber Situational Awareness (HACSAW) research environment and evaluated on structured network sensor logs collected from Defense Research and Engineering Network (DREN) sites using HPC resources at the U.S. Army Engineer Research and Development Center DoD Supercomputing Resource Center (ERDC DSRC). To date, MADHAT has analyzed logs with over 650 million entries.

Cyber security, Tensor decomposition, graph analyt↗
DOE OSTI2026

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Modeling Framework for Bulk Electric Grid Impacts from HEMP E1 and E3 Effects (Tasks 3.1 Final Report)

This report presents a framework to evaluate the impact of a high-altitude electromagnetic pulse (HEMP) event on a bulk electric power grid. This report limits itself to modeling the impact of EMP E1 and E3 components. The co-simulation of E1 and E3 is presented in detail, and the focus of the paper is on the framework rather than actual results. This approach is highly conservative as E1 and E3 are not maximized with the same event characteristics and may only slightly overlap. The actual results shown in this report are based on a synthetic grid with synthetic data and a limited exemplary EMP model. The framework presented can be leveraged and used to analyze the impact of other threat scenarios, both manmade and natural disasters. This report d escribes a Monte-Carlo based methodology to probabilistically quantify the transient response of the power grid to a HEMP event. The approach uses multiple fundamental steps to characterize the system response to HEMP events, focused on the E1 and E3 components of the event. 1) Obtain component failure data related to HEMP events testing of components and creating component failure models. Use the component failure model to create component failure conditional probability density function (PDF) that is a function of the HEMP induced terminal voltage. 2) Model HEMP scenarios and calculate the E1 coupled voltage profiles seen by all system components. Model the same HEMP scenarios and calculate the transformer reactive power consumption profiles due to E3. 3) Sample each component failure PDF to determine which grid components will fail, due to the E1 voltage spike, for each scenario. 4) Perform dynamic simulations that incorporate the predicted component failures from E1 and reactive power consumption at each transformer affected by E3. These simulations allow for secondary transients to affect the relays/protection remaining in service which can lead to cascading outages. 5) Identify the locations and amount of load lost for each scenario through grid dynamic simulation. This can be an indication of the immediate grid impacts from a HEMP event. In addition, perform more detailed analysis to determine critical nodes and system trends. 6) To help realize the longer-term impacts, a security constrained alternating current optimal power flow (ACOPF) is run to maximize critical load served. This report describes a modeling framework to assess the systemic grid impacts due to a HEMP event. This stochastic simulation framework generates a large amount of data for each Monte Carlo replication, including HEMP location and characteristics, relay and component failures, E3 GIC profiles, cascading dynamics including voltage and frequency over time, and final system state. This data can then be analyzed to identify trends, e.g., unique system behavior modes or critical components whose failure is more likely to cause serious systemic effects. The proposed analysis process is demonstrated on a representative system. In order to draw realistic conclusions of the impact of a HEMP event on the grid, a significant amount of work remains with respect to modeling the impact on various grid components.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Toward Interactive Scenario Analysis and Exploration

As Modeling and Simulation (M&S) tools have matured, their applicability and importance have increased across many national security challenges. In particular, they provide a way to test how something may behave without the need to do real world testing. However, current and future changes across several factors including capabilities, policy, and funding are driving a need for rapid response or evaluation in ways that many M&S tools cannot address. Issues around large data, computational requirements, delivery mechanisms, and analyst involvement already exist and pose significant challenges. Furthermore, rising expectations, rising input complexity, and increasing depth of analysis will only increase the difficulty of these challenges. In this study we examine whether innovations in M&S software coupled with advances in ''cloud'' computing and ''big-data'' methodologies can overcome many of these challenges. In particular, we propose a simple, horizontally-scalable distributed computing environment that could provide the foundation (i.e. ''cloud'') for next-generation M&S-based applications based on the notion of ''parallel multi-simulation''. In our context, the goal of parallel multi- simulation is to consider as many simultaneous paths of execution as possible. Therefore, with sufficient resources, the complexity is dominated by the cost of single scenario runs as opposed to the number of runs required. We show the feasibility of this architecture through a stable prototype implementation coupled with the Umbra Simulation Framework [6]. Finally, we highlight the utility through multiple novel analysis tools and by showing the performance improvement compared to existing tools.

97 MATHEMATICS AND COMPUTING↗