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All sources NASA NTRS DOE OSTI

DOE OSTI2026

Holistic Transportation and Energy Modeling

This project advances the development and application of the TEMPO transportation energy systems model to support DOE analysis of evolving mobility futures. Recent work has focused on improving model transparency, performance, and fidelity through a redesigned software architecture and updated technology adoption scenarios aligned with the latest data and assumptions. Ongoing efforts aim to expand TEMPO's ability to assess transportation affordability and consumer decision-making, including vehicle ownership dynamics and distributional impacts across households. These enhancements position TEMPO to better inform policy and R&D decisions by providing more behaviorally realistic and policy-relevant insights into transportation energy use, technology adoption, and system-level outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

First Principles Prediction of Structure, Structure Selectivity, and Thermodynamic Stability under Realistic Conditions

Novel materials are often the enabler for new energy technologies. In ab-initio computational materials science, method are developed to predict the behavior of materials starting from the laws of physics, so that properties can be predicted before compounds have to be synthesized and tested. As such, a virtual materials laboratory can be constructed, saving time and money. The objectives of this program were to develop first-principles theory to predict the structure and thermodynamic stability of materials. Since its inception the program focused on the development of the cluster expansion to deal with the increased complexity of complex oxides. This research led to the incorporation of vibrational degrees of freedom in ab-initio thermodynamics, developed methods for multi-component cluster expansions, included the explicit configurational degrees of freedom of localized electrons, developed the formalism for stability in aqueous environments, and culminated in the first ever approach to produce exact ground state predictions of the cluster expansion. Many of these methods have been disseminated to the larger theory community through the Materials Project, pymatgen software, or individual codes. We summarize three of the main accomplishments.

36 MATERIALS SCIENCE↗

DOE OSTI2016

SU-F-T-490: Separating Effects Influencing Detector Response in Small MV Photon Fields

Purpose: Different detector properties influence their responses especially in field sizes below the lateral electron range. Due to the finite active volume, the detector density and electron perturbation at other structural parts, the response factor is in general field size dependent. We aimed to visualize and separate the main effects contributing to detector behavior for a variety of detector types. This was achieved in an experimental setup, shielding the field center. Thus, effects caused by scattered radiation could be examined separately. Methods: Signal ratios for field sizes down to 8 mm (SSD 90 cm, water depth 10 cm) of a 6MV beam from a Siemens Primus LINAC were recorded with several detectors: PTW microDiamond and PinPoint ionization chamber, shielded diodes (PTW P-60008, IBA PFD and SNC Edge) and unshielded diodes (PTW E-60012 and IBA SFD). Measurements were carried out in open fields and with an aluminum pole of 4 mm diameter as a central block. The geometric volume effect was calculated from profiles obtained with Gafchromic EBT3 film, evaluated using FilmQA Pro software (Ashland, USA). Results: Volume corrections were 1.7% at maximum. After correction, in small open fields, unshielded diodes showed a lower response than the diamond, i.e. diamond detector over-response seems to be higher than that for unshielded diodes. Beneath the block, this behavior was amplified by a factor of 2. For the shielded diodes, the overresponse for small open fields could be confirmed. However their lateral response behavior was strongly type dependent, e.g. the signal ratio dropped from 1.02 to 0.98 for the P-60008 diode. Conclusion: The lateral detector response was experimentally examined. Detector volume and density alone do not fully account for the field size dependence of detector response. Detector construction details play a major role, especially for shielded diodes.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2020

Vulnerabilities in Artificial Intelligence and Machine Learning Applications and Data

Artificial intelligence (AI) applications driven by machine learning (ML) are transformational technologies within the international nuclear security regime. Advancements realized by AI—faster and improved data insights, more efficient and automated processes, reductions in human error—enable nuclear security applications such as behavior analysis for insider threat mitigation, source tracking of stolen nuclear material, and facial recognition software for physical protection. In addition to the advantages, however, there are also inherent vulnerabilities and threats associated with its use and risk mitigations must be built into any AI/ML-enabled systems. This work provides a background on AI and ML and different data types used in the field, including open-source intelligence information (OSINT) that is discoverable by AI tools and application data that are used by AI tools for decision-making and automation. Current and potential AI applications and vulnerabilities related to their use within the nuclear security regime are also discussed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2011

Skin dose mapping for fluoroscopically guided interventions

Purpose: To introduce a new skin dose mapping software system for interventional fluoroscopy dose assessment and to analyze the benefits and limitations of patient-phantom matching. Methods: In this study, a new software system was developed for visualizing patient skin dose during interventional fluoroscopy procedures. The system works by translating the reference point air kerma to the location of the patient's skin, which is represented by a computational model. In order to orient the model with the x-ray source, geometric parameters found within the radiation dose structured report (RDSR) are used along with a limited number of in-clinic measurements. The output of the system is a visual indication of skin dose mapped onto an anthropomorphic model at a resolution of 5 mm. In order to determine if patient-dependent and patient-sculpted models increase accuracy, peak skin dose was calculated for each of 26 patient-specific models and compared with doses calculated using an elliptical stylized model, a reference hybrid model, a matched patient-dependent model and one patient-sculpted model. Results were analyzed in terms of a percent difference using the doses calculated using the patient-specific model as the true standard. Results: Anthropometric matching, including the use of both patient-dependent and patient-sculpted phantoms, was shown most beneficial for left lateral and anterior-posterior projections. In these cases, the percent difference using a reference model was between 8 and 20%, using a patient-dependent model between 7 and 15%, and using a patient-sculpted model between 3 and 7%. Under the table tube configurations produced errors less than 5% in most situations due to the flattening affects of the table and pad, and the fact that table height is the main determination of source-to-skin distance for these configurations. In addition to these results, several skin dose maps were produced and a prototype display system was placed on the in-clinic monitor of an interventional fluoroscopy system. Conclusions: The skin dose mapping program developed in this work represents a new tool that, as the RDSR becomes available through automated export or real-time streaming, can provide the interventional physician information needed to modify behavior when clinically appropriate. The program is nonproprietary and transferable, and also functions independent to the software systems already installed on the control room workstation. The next step will be clinical implementation where the workflow will be optimized along with further analysis of real-time capabilities.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2015

WE-G-BRA-06: Application of Systems and Control Theory-Based Hazard Analysis to Radiotherapy

Purpose: The process of delivering radiation occurs in a complex socio-technical system heavily reliant on human operators. Furthermore, both humans and software are notoriously challenging to account for in traditional hazard analysis models. High reliability industries such as aviation have approached this problem through using hazard analysis techniques grounded in systems and control theory. The purpose of this work is to apply the Systems Theoretic Accident Model Processes (STAMP) hazard model to radiotherapy. In particular, the System-Theoretic Process Analysis (STPA) approach is used to perform a hazard analysis of a proposed on-line adaptive cranial radiosurgery procedure that omits the CT Simulation step and uses only CBCT for planning, localization, and treatment. Methods: The STPA procedure first requires the definition of high-level accidents and hazards leading to those accidents. From there, hierarchical control structures were created followed by the identification and description of control actions for each control structure. Utilizing these control structures, unsafe states of each control action were created. Scenarios contributing to unsafe control action states were then identified and translated into system requirements to constrain process behavior within safe boundaries. Results: Ten control structures were created for this new CBCT-only process which covered the areas of hospital and department management, treatment design and delivery, and vendor service. Twenty three control actions were identified that contributed to over 80 unsafe states of those control actions resulting in over 220 failure scenarios. Conclusion: The interaction of people, hardware, and software are highlighted through the STPA approach. STPA provides a hierarchical model for understanding the role of management decisions in impacting system safety so that a process design requirement can be traced back to the hazard and accident that it is intended to mitigate. Varian Medical Systems, Inc.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Digital Twin for Chemical Science (DTCS) v0.01

Directly visualizing the trajectories of chemistry can unravel novel insights into the behavior of catalysts, gas phase reactions, photo-induced dynamics, and building blocks for quantum information processing. The ability of explicitly identifying, tracking, and tagging the exchange of matter, hence the annihilation and creation of new chemical species, can be best realized through a close coupling of theory and experiment. While the synchrotron-based characterization facilities propelled rapidly in its hardware, providing higher brightness, better resolution, and more precision, the software infrastructure is lagging. We developed DTCS (Digital Twin for Chemical Science) v.01, a central platform that faithfully mimics advanced instrumentations in Scientific User Facilities, by solving a variety of technical challenges in data acquisition, analysis, and model-driven interpretation. Rooted in physics and accelerated by AI, we validated this concept by direct comparison with precise experimental X-ray Photoelectron Spectroscopy (XPS) observations using a ubiquitous metal-water interfacial scenario, i.e., Ag/H2O as our main narrative. The DTCS v.01 input mirrors how the bench chemists work, with the output directly linked to the end station computer, thereby providing a user-friendly, knowledge-driven, and accessible user experience with mechanistic insights standardized in a way that are ready to be published, versioned, and transferred flexibly.

Qian, Jin↗

DOE OSTI2011

XIM-A VIRTUAL X-RAY OBSERVATORY: INVESTIGATING THE X-RAY APPEARANCE AND LINE PROFILE FUNCTION OF VORTEX RINGS IN GALAXY CLUSTERS

We present virtual observations of a simulated vortex ring in a galaxy cluster (such as the Virgo Cluster, where such a ring has been observed), using the virtual X-ray observatory software XIM. We derive the expected surface brightness distributions and color maps for a vortex seen at different line-of-sight angles. We present the line profile function {phi}({delta}{nu}) for the velocity field of a vortex ring as derived from the observations and show that the line core has a frequency dependence of {phi} {proportional_to} ({delta}{nu}/{nu}{sub 0}){sup -2} and derive this form of the line profile from the analytic description of the asymptotic behavior of the velocity field of a vortex ring. We discuss further examples of the application of XIM to studies of galaxy clusters and present the capabilities and methodology of the publicly available code XIM.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Battery Thermal Characterization

A well-designed thermal management system is critical to the life and performance of electric-drive vehicles (EDVs) hybrids (HEVs), plug-in hybrids (PHEVs), and all-electric vehicles (EVs). Temperature and temperature uniformity both significantly affect the performance, lifespan, and safety of vehicle energy storage devices. NREL conducts thermal management research and development (R&D) to optimize battery performance and extend useful life. A recognized leader in battery thermal analysis and characterization, NREL evaluates electrical and thermal performance of battery cells, modules, and packs, full energy storage systems, and the interaction of these systems with other vehicle components. The lab's performance assessments factor in the design of the thermal management system, the thermal behavior of the cell, battery lifespan, and safety of the energy storage system, as well as full integration into a vehicle. The lithium-ion (Li-ion) batteries found in most of today's electric-drive vehicles are smaller and more lightweight than previous nickel-metal hydride (NiMH) technology, but they are also more sensitive to overheating, overcharging, and extreme spikes in temperature known as thermal runaway. High temperatures diminish battery life and increase battery replacement costs, while low temperatures decrease battery power and capacity, all of which impact vehicle range, performance, and affordability. NREL's breakthrough research is focused on reducing thermal barriers to achieve more uniform temperatures. NREL uses its R&D 100 Award-winning Isothermal Battery Calorimeters, the only instruments in the world capable of such precise thermal measurements, for much of this research. Calorimeter readings are paired with thermal imaging of batteries using infrared cameras to evaluate battery temperature distribution. In addition, NREL is working with industry to develop computer-aided engineering software tools to optimize thermal management of batteries. NREL's analysis for the U.S. Advanced Battery Consortium (USABC) show that optimized thermal management can increase battery power by more than 10%. Without proper thermal management, an EDV battery can last more than 10 years in a temperate climate, like in Minnesota, but only 7 years in a hot climate, such as in Arizona. In extreme instances, battery overheating can pose safety hazards, including fires. Performance: Maintaining desired temperature ranges is critical in optimizing EDV battery storage capacity, lifespan, and performance, and eventually impacts cost and consumer acceptance. NREL's breakthrough research focuses on achieving more uniform temperatures while a vehicle is in motion and actively generating heat, as well as when it is parked and exposed to ambient temperatures over prolonged periods of time. Safety: Most energy storage systems deliver maximum performance at higher temperatures. However, this extreme heat can overload systems and create dangerous conditions. NREL evaluation helps to more effectively regulate thermal characteristics, providing greater safeguards and stronger performance. NREL has invented a device that emulates internal short circuits in batteries to better understand how to prevent future failures and related hazards.

25 ENERGY STORAGE↗

DOE OSTI2015

Atmospheric-pressure plasma jet characterization and applications on melanoma cancer treatment (B/16-F10)

A new approach in medicine is the use of cold plasma for various applications such as sterilization blood coagulation and cancer cell treatment. In this paper, a pin-to-hole plasma jet for biological applications has been designed and manufactured and characterized. The characterization includes power consumption via Lissajous method, thermal behavior of atmospheric-pressure plasma jet by using Infra-red camera as a novel method and using Speicair software to determine vibrational and transitional temperatures, and optical emission spectroscopy to determine the generated species. Treatment of Melanoma cancer cells (B16/F10) was also implemented, and tetrazolium salt dye (MTT assay) and flow cytometry were used to evaluate viability. Effect of ultraviolet photons on cancerous cells was also observed using an MgF{sub 2} crystal with MTT assay. Finally, in-vivo studies on C57 type mice were also done in order to have a better understanding of the effects in real conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Software Defined Architectures for Data Analytics

Data analytics applications increasingly are complex workflows composed of phases with very different program behaviors (e.g., graph algorithms and machine learning, algorithms operating on sparse an dense data structures, etc). To reach the levels of efficiency required to process these workflows in real time, upcoming architectures will need to leverage even more workload specialization. If, at one end, we may find even more heterogenous processors composed by a myriad of specialized processing elements, at the other end we may see novel reconfigurable architectures, composed of sets of functional units and memories interconnected with (re)configurable on-chip networks, able to adapt dynamically to adapt the workload characteristics. Field Programmable Gate Arrays are more and more used for accelerating various workloads and, in particular, inferencing in machine learning, providing higher efficiency than other solutions. However, their fine grained nature still leads to issues for the design software and still makes dynamic reconfiguration impractical. Future, more coarse-grained architectures could offer the features to execute diverse workloads at high efficiency while providing better reconfiguration mechanisms for dynamic adaptability. Nevertheless, we argue that the challenges for reconfigurable computing remain in the software. In this position paper, we describe a possible toolchain for reconfigurable architectures targeted at data analytics.

FPGA, Dataflow, Reconfigurable Architectures, Soft↗

DOE OSTI2019

Behavior specification, finding main, and call graph visualizations

A process transforms compiled software into a semantic form. The process transforms the code into a semantic form. The process analyzes behavior functionality by processing precise programming behavior abstractions stored in a memory and classifies the code as malware based on the code behavior. Another method identifies the starting point of execution of a compiled program. The method calculates a complexity measure by calculating the number of potential execution paths of local functions; identifies the number of arguments passed to local functions; and identifies the starting point of execution of the compiled program. Another method provides interactive, dynamic visualization of a group of related functions wherein a user can explore the rendered graph and select a specific function and display functions that are color coded by their ancestral relation and their function call distance to the selected function.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Data-Conforming Data-Driven Control: Avoiding Premature Generalizations Beyond Data

Data-driven and adaptive control approaches face the problem of introducing sudden distributional shifts beyond the distribution of data encountered during learning. Therefore, they are prone to invalidating the very assumptions used in their own construction. This is due to the linearity of the underlying system, inherently assumed and formulated in most data-driven control approaches, which may falsely generalize the behavior of the system beyond the behavior experienced in the data. This article seeks to mitigate these problems by enforcing consistency of the newly designed closed-loop systems with data and slowing down any distributional shifts in the joint state-input space. This is achieved through incorporating affine regularization terms and linear matrix inequality constraints to data-driven approaches, resulting in convex semi-definite programs that can be efficiently solved by standard software packages. We discuss the optimality conditions of these programs and then conclude this article with a numerical example that further highlights the problem of premature generalization beyond data and shows the effectiveness of our proposed approaches in enhancing the safety of data-driven control methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Effect of Initial FeO Content and CaO:SiO{sub 2} Ratio on the Reduction Smelting Kinetics of the CaO-SiO{sub 2}-MgO{sub satd.}-FeO Slag System

The effect of the initial FeO content and CaO:SiO{sub 2} ratio (CaO mass pct/SiO{sub 2} mass pct) on the reduction smelting of FeO with carbon flake addition is investigated in the CaO-MgO{sub satd.}-SiO{sub 2}-FeO slag system at 1823 K (1550 °C). Carbon rapidly reacted with FeO in the molten slag, causing both foaming and compositional changes in the slag. As FeO is reduced, the MgO saturation is modified, and solid precipitants, including MgO and other complex oxides, were observed, which significantly affected the slag properties, including the viscosity and foaming behavior. The solid-phase fraction and viscosity were estimated from changes in the measured FeO content over time using the thermochemical software FactSage. The iron recovery, which is distinguished from the amount of reduced Fe droplets, showed opposite behavior to the measured maximum foaming height and modified foaming index. According to the FeO mass transfer coefficient considering slag foaming at various initial FeO contents and CaO:SiO{sub 2} ratios, the reduction rate was optimal at higher initial FeO contents and a CaO:SiO{sub 2} ratio of 2.0, which did not correspond to the optimal iron recovery at an initial FeO content of 44 mass pct and above and a CaO:SiO{sub 2} ratio of 1.2. The results showed that slag foaming may increase the reduction kinetics, but the slag composition needs to be optimized for greater iron recovery.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Benchmark Generation and Simulation at Extreme Scale

The path to extreme scale high-performance computing (HPC) poses several challenges related to power, performance, resilience, productivity, programmability, data movement, and data management. Investigating the performance of parallel applications at scale on future architectures and the performance impact of different architectural choices is an important component of HPC hardware/software co-design. Simulations using models of future HPC systems and communication traces from applications running on existing HPC systems can offer an insight into the performance of future architectures. This work targets technology developed for scalable application tracing of communication events. It focuses on extreme-scale simulation of HPC applications and their communication behavior via lightweight parallel discrete event simulation for performance estimation and evaluation. Instead of simply replaying a trace within a simulator, this work promotes the generation of a benchmark from traces. This benchmark is subsequently exposed to simulation using models to reflect the performance characteristics of future-generation HPC systems. This technique provides a number of benefits, such as eliminating the data intensive trace replay and enabling simulations at different scales. The presented work features novel software co-design aspects, combining the ScalaTrace tool to generate scalable trace files, the ScalaBenchGen tool to generate the benchmark, and the xSim tool to assess the benchmark characteristics within a simulator.

Lagadapati, Mahesh↗

DOE OSTI2019

An Integrated Numerical Method to Predict the Strain Sensing Behavior of Flexible Conductive Fibers under Electric–Thermal Conditions

Flexible conductive textiles have attracted an increasing amount of attention due to being flexible and stretchable with multi-functions, in addition to the strain sensing function. In this paper, an integrated numerical method is established to predict the strain sensing behavior of PPy-coated flexible conductive fibers. Based on our previous investigation on the strain sensing behavior of the PPy-coated elastic conductive fibers, it has been known that the main strain sensing mechanisms of the conductive fibers are micro-cracks opening under stretching and closing under unloading. Therefore, in the numerical approach, extended finite element method is used to simulate the multi-crack initiation and propagation. Then, by establishing a representative element model including a single crack, the resistance variation with the increase in crack width/depth can be obtained using the electric–thermal package in ABAQUS software. Combining the relationship between crack width and strain, the relationship between fractional increment in resistance (ΔR/R{sub 0}) and the strain can be obtained. The prediction of the fractional increment in resistance (ΔR/R{sub 0}) versus strain is consistent with the experimental results of PPy-coated Lycra fibers. The new integrated method is further verified by experimental results of PPy-coated XLA fibers, showing that the integrated numerical approach can capture the complicated strain sensing mechanisms of PPy-coated elastic fibers and predict the strain sensing behavior of flexible conductive fibers. This approach will make it possible to shorten the period, and reduce the cost in R&D of the PPy-coated electrically conductive fibers, comparing with the corresponding experimental work.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Comparison of subchannel and averaged channel thermal-hydraulic descriptions on coupled pin-by-pin neutronic calculations

Best-estimate transient analysis of Light Water Reactors (LWRs) requires high accuracy code systems solving neutronics (NK), thermal-hydraulics (TH) and thermal-mechanics to model the core behavior. For long time, nodal diffusion methods for solution of the transport equation using assembly size computational meshes have been applied neglecting the details within the fuel assembly, or using 'pin power reconstruction' techniques to predict those details. Moreover, the multiphysics analysis has been commonly performed coupling those neutronic diffusion methods to thermal-hydraulic system codes using a nodalization of several fuel assemblies per computational node without taking into account the effects that this type of averaging can have on the results obtained. This paper presents the work accomplished with the coupled system COBAYA4/CTF for a preliminary analysis of the effect of the different accuracy levels in the NK and TH domain. COBAYA4 is a neutronic code able to solve the diffusion equation at two resolution levels, nodal and pin by pin (PbP). CTF is a thermo-hydraulic code able to solve the coolant conservation equations also at two levels, channel (fuel assembly averaged solution) and sub-channel (real cooling channel) level. The coupled system COBAYA4/CTF is used through SALOME platform, i.e. SALOME is the software able to map conveniently the NK and TH meshes. This coupling allows combining different resolution levels for NK and TH problems. Therefore, the study of the effect of using different resolutions for the NK and TH nodalizations has been performed applying the system to a fuel assembly with selected boundary conditions. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Asynchronous Runtimes in Action: An Introspective Framework for a Next Gen Runtime

One of the most critical challenges that new high performance systems face is the lack of system software support for these large scale systems. Investment on system stack components is essential in the development, debugging and optimization of the new emerging programming models. These emerging models have the promise to better utilize the vast hardware resources available in current and future systems. To aid in the development of applications and new system stacks, runtimes, as instances of their respective execution models, need to produce facilities to introspect their inner workings and allow an indepth attribution of performance bottlenecks and computational patterns. In other words, the runtime systems need to reduce their opacity to observers so that users of a novel program execution model can adapt their designs to fit the intended model usage, regardless of the layer that they are working on. This design/development loop (akin to co-design) enables synergistic opportunities across the entire computational stack. This paper presents the design and implementation of a simple “gray” box performance attribution harness running inside a fine grain runtime system: the Open Community Runtime (OCR). We showcase what such a framework can indicate regarding the runtime behavior while running at scale. To this end, we have designed a set of synthetic scenarios aimed to test the runtime at their best and worst cases. We present an analysis of the most important runtime features, properties and idiosyncrasies that will affect the development of new runtime features, algorithmic selection, and application development.

high performance distributed runtimes↗