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Thiis presentation shows the character of an integral experiment. It covers the question why Godiva 4? Additionally, this presentation touches on the IER 498 benchmark quantity, activities facilitated by IER 498, proposed CED-2 test matrix, and what happened during the IER 498’s gap year.
Preserving experimental data is essential for supporting advancements in nuclear science and ensuring the longevity of Idaho National Laboratory's contributions to reactor technology and safety. This report provides a comprehensive guide to best practices for experimental data management and preservation, focusing on standardized data formats, redundancy in storage, metadata documentation, and alignment with international standards. By following these recommendations, experimentalists and reactor operators can enhance the accessibility, reproducibility, and utility of critical datasets for regulatory review, validation computational methods, and future research.
Open, tabular electronic health record (EHR) datasets such as MIMIC-III and MIMIC-IV have become critical resources for developing machine learning (ML) models addressing clinical prediction tasks, including hospital readmission, length of stay, and in-hospital mortality (IHM). While MIMIC-III has benefited from well-established preprocessing pipelines and standardized feature sets, MIMIC-IV remains comparatively challenging to work with because there are no standardized benchmarks to support reproducibility and comparability across studies. To address this limitation, we present a rigorously curated MIMIC-IV custom feature set optimized for IHM prediction, constructed through a reproducible preprocessing pipeline and feature selection strategy.
This presentation provides a comprehensive comparison of inverter-based resource (IBR) technical requirements across multiple international grid codes - including IEEE 2800, ESO, EirGrid, and Malawi's evolving regulatory framework - to support capacity building for electricity-sector institutions in Malawi. It highlights key performance expectations for grid-following (GFL) inverters across critical domains such as primary and fast frequency response, ramping behavior, frequency and voltage ride-through capabilities, reactive power and voltage control, ROCOF withstand, phase jump tolerance, system strength considerations, protection schemes, and dynamic modeling requirements. Emphasizing a "Do no harm, do something, do more" philosophy, the document synthesizes best practices and operational benchmarks to guide the integration and stability of inverter-based resources within Malawi's power system. The presentation forms part of the SABESS Center of Excellence initiative supported by the Global Energy Alliance for People and the Planet.
High-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. Data analysis has been accelerated in recent years by the adoption of artificial intelligence (AI) and machine learning (ML) techniques by biomedical researchers. In space biology research, RNAseq datasets from space-flown experimental samples are critical for characterizing the gene expression aberrations associated with exposure to spaceflight stressors. However, space biological experiments tend to be very low sample size, so identifying proper AI/ML algorithms for sequencing data analysis is an ongoing challenge since these algorithms typically require large sample size. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML”, focused on creating datasets meant for three main applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. These scientific benchmarks consist of an AI-ready dataset and a reference implementation on a specific scientific question. In this work, we focused on generating standardized datasets to allow the scientific community to benchmark AI/ML algorithms in the domain of space biology. We present here a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data as a collaboration between the NASA AI4LS (Artificial Intelligence for Life Sciences) working group. and NASA’s SMD. This dataset consists of space-flown and ground control mouse liver found in the NASA GeneLab omics database. However, to amplify the small sample number (n=112 samples) for ML purposes, we employ Gaussian noise and a generative adversarial network to extend this dataset to 6,000 synthetic samples, matching the original gene expression characteristics.
Abstract Detailed design of REBa 2 Cu 3 O 7 − x (REBCO)-based magnets ideally relies on knowledge of the full angular and wide temperature range characterization of the critical current I c of the REBCO coated conductors (CC) at high magnetic fields. In practice, however, obtaining I c ( B , T , θ ) data by the commonly used electrical transport technique is expensive, tedious, and difficult, due to high critical current values that exceed 2000 A for B | | a b -plane ( θ = 90 deg). The conductors are often damaged during angular transport measurements at angles approaching the ab -plane. Therefore, so far, REBCO magnets have been designed without full I c ( B , T , θ ) data sets. Here, we present J c ( B , T , θ ) results for more than twenty samples of CC all made to the same advanced pinning specification produced by SuperPower Inc. For this, we employed torque magnetometry, benchmarking the results to transport I c measurements mostly made away from ab -plane, finding good agreement with scaling factors ≈1–1.3. What is striking is the huge variety of properties exhibited by the samples, even for CC made recently. Given the huge attention now being paid to the effects of screening currents and to the torques generated by offsets between the tape plane and the local magnetic field vector, our data set suggests some caution in detailed design of such magnets without having data of the type presented here.
Focused Very-High Energy Electron (VHEE, 50–300 MeV) and Ultra-High Energy Electron (UHEE, > 300 MeV) beams can accurately target both large and deeply seated human tumors with high sparing properties, while avoiding the spatial requirements and cost of proton and heavy ion facilities. Advanced testing phases are underway at the CLEAR facilities at CERN (Switzerland), NLCTA at Stanford (USA), and SPARC at INFN (Italy), aiming to accelerate the transition to clinical application. Currently, Monte Carlo (MC) transport is the sole paradigm supporting preclinical trials and imminent clinical deployment. In this paper, we propose an alternative: the first extension of the nuclear-reactor deterministic chain Njoy-Dragon for VHEE and UHEE applications. We have extended the Boltzmann-Fokker-Planck (BFP) multigroup formalism and validated it using standard radio-oncology benchmarks, complex assemblies with a wide range of atomic numbers, and comprehensive irradiation of the entire periodic table. We report that 99% of water voxels exhibit a BFP-MC deviation below 2% for electron energies under 1.5 GeV. Additionally, we demonstrate that at least 97% of voxels of bone, lung, adipose tissue, muscle, soft tissue, tumor, steel, and aluminum meet the same criterion between 50 MeV and 1.5 GeV. For water, the thorax, and the breast intra-operative benchmark, typical average BFP-MC deviations of 0.3% and 0.4% were observed at 300 MeV and 1 GeV, respectively. By irradiating the entire periodic table, we observed similar performance between lithium (Z = 3) and cerium (Z = 58). Deficiencies observed between praseodymium (Z = 59) and einsteinium (Z = 99) have been reported, analyzed, and quantified, offering critical insights for the ongoing development of the Evaluated Nuclear Data File mode in NJOY.
Employee Assistance Program (EAP) officers, as well as personnel in other disciplines from eight NASA Centers, attended this breakout session. Ms. Brenda Blair, MA, CEAP, a guest speaker at the conference, also attended as a consultant. Representatives from the NASA Centers introduced themselves and spoke briefly about their programs. In a discussion related to the conference theme on benchmarking, quality control issues within the EAP community and adequate documentation of cases were addressed. Disposition and provision for quality assurance checks for EAP providers in single person offices were also discussed. Ms. Blair presented methods for consulting with other NASA personnel in single person EAP offices as a quality control measure. EAP intervention in critical incidents was discussed. The question of whether EAP assistance is an asset or a potential liability in those situations was addressed. Suggestions were made of topics for future EAP video-teleconference topics. A program on EAP ethics was planned for a September video teleconference. Each person was asked to provide intake forms they use to Mr. Gettleman or Ms. Blair. Ms. Blair said she would review the forms to ensure that adequate notification is provided to the client for confidentiality. She would also review them to ensure they have adequate limits of confidentiality--a topic for future video teleconferencing. Mr. Gettleman described the NASA initiative to reduce stresses in the workplace, and the activities of an ad-hoc EAP group that will make recommendations to NASA senior management. Alternative training methods were discussed for reaching target audiences such as employees at risk, supervisors, and others. Pfc. David A. Pendleton, Victim Assistance Coordinator, U.S. Capitol Police. U.S. House of Representatives made a special presentation. Pfc. Pendleton was on duty during the tragic shooting of two Federal guards at the U.S. Capitol. He related the events immediately after the incident. He described the nature and structure of the EAP's and the separate nature of the House and Senate programs. This episode was a particularly difficult situation as large numbers of tourists were involved. William S. Barry, MD, the new Manager of the NASA Occupational Health Program Office was introduced to those attending the breakout session.
The identification of porosity, geometric noncompliance, and other defect types are critical to the qualification of materials and components. X-ray radiographic nondestructive testing is a common industrial inspection method for process quality control and component qualification and certification. Digital radiography provides a quick and efficient alternative when compared to traditional film-based inspection. The quality of radiographic inspection is dependent on equipment specifications, such as the source spot size and detector pixel size, and the specific parameters selected for use for the radiographic technique. To evaluate if an x-ray system and technique is sufficient for a given requirement, a radiographic image quality indicator (IQI) can be used. Radiographic IQIs in hard to machine materials or hard to manufacture defects can be time consuming and expensive to manufacture. This study was conducted to evaluate current Savannah River National Laboratory (SRNL) x-ray imaging systems with a custom tantalum IQI and using Monte Carlo simulations to predict the performance of future systems. The tantalum IQI was tested using a Siefert Isovolt 420 keV x-ray tube with a Perkin Elmer XRD 1611 flat panel with 100-micron pixels. Using the Monte Carlo N-Particle transport software, the radiographic tally was used to simulate the photon flux through an identical tantalum IQI. These simulations provided a benchmark as to the best theoretical identification on a given system using our tantalum IQI. The simulations were refined to match SRNL’s current systems’ noise levels, leading to confidence in their ability to predict the performance of other systems that may be purchased and deployed in the future at the Savannah River Site. Future studies will be conducted to prove this research can be extended to artificially evaluate the ability for systems to identify critical defect sizes through x-ray radiographic inspection, drastically reducing the cost and time burdens of producing high-fidelity radiographic test articles.
Bayesian evaluation of resolved resonance region (RRR) nuclear data has historically been carried out using the generalized least squares (GLS) formalism, as implemented in, e.g., SAMMY. We have recently developed a prototype of Bayesian Monte Carlo (BMC) evaluation framework, implemented using a Markov Chain Monte Carlo (MCMC) method with a Metropolis-Hastings (MH) acceptance criterion. This was done in order to remove the approximations underlying the conventional GLS evaluations, namely, the linear approximation, and the approximation that all probability density functions (PDFs) are of the normal kind. Recent works by others have used similar stochastic approaches to quantify cross section uncertainties from ENDF evaluated co-variances, and/or, from integral benchmark data, but those have not been conceived as an evaluation framework like the one presented here.
A series of uni-element rocket injector studies were completed to provide benchmark quality data needed to validate computational fluid dynamic models. A shear coaxial injector geometry was selected as the primary injector for study using gaseous hydrogen/oxygen and gaseous hydrogen/liquid oxygen propellants. Emphasis was placed on the use of non-intrusive diagnostic techniques to characterize the flowfields inside an optically-accessible rocket chamber. Measurements of the velocity and species fields were obtained using laser velocimetry and Raman spectroscopy, respectively Qualitative flame shape information was also obtained using laser-induced fluorescence excited from OH radicals and laser light scattering studies of aluminum oxide particle seeded combusting flows. The gaseous hydrogen/liquid oxygen propellant studies for the shear coaxial injector focused on breakup mechanisms associated with the liquid oxygen jet under sub-critical pressure conditions. Laser sheet illumination techniques were used to visualize the core region of the jet and a Phase Doppler Particle Analyzer was utilized for drop velocity, size and size distribution characterization. The results of these studies indicated that the shear coaxial geometry configuration was a relatively poor injector in terms of mixing. The oxygen core was observed to extend well downstream of the injector and a significant fraction of the mixing occurred in the near nozzle region where measurements were not possible to obtain Detailed velocity and species measurements were obtained to allow CFD model validation and this set of benchmark data represents the most comprehensive data set available to date As an extension of the investigation, a series of gas/gas injector studies were conducted in support of the X-33 Reusable Launch Vehicle program. A Gas/Gas Injector Technology team was formed consisting of the Marshall Space Flight Center, the NASA Lewis Research Center, Rocketdyne and Penn State. Injector geometries studied under this task included shear and swirl coaxial configurations as well as an impinging jet injector.
Plastic scintillators, a class of solid-state materials used for radiation detection, were additively manufactured with vat photopolymerization. The photopolymer resins consisted of a primary dopant and a secondary dopant dissolved in a bisphenol A ethoxylate diacrylate-based matrix. The absorptive dopants significantly influence important print parameters, for example, secondary dopants decrease the light penetration depth by a factor > 12×. The primary dopant 2,5-diphenyloxazole had minimal impact on the printing process even when loaded at 25 % by mass of the resin. Working curve measurements, which relate energy dose to cure depth, were performed as a function of feature size to further assess the influence of dopants. Photopatterns smaller than 150 µm width had apparent increases in critical energy dose compared to larger photopatterns, while all resins maintained printed features in line gratings with 50 µm of separation. Printed scintillator monoliths were compared to scintillators cast by traditional molding, demonstrating that the layer-by-layer printing process does not decrease scintillation response. In conclusion, a maximum light output of 31 % of a benchmark plastic scintillator (EJ-200) and successful pulse shape discrimination were achieved with 20 % by mass 2,5-diphenyloxazole as the primary dopant and 0.1 % by mass 9,9-dimethyl-2,7-distyrylfluorene as the secondary dopant in printed scintillator samples.
This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.
A new 181 Ta neutron resolved resonance region evaluation has been performed from the thermal energy range up to approximately 2.5 keV. The R-matrix SAMMY code was used with the Reich–Moore approximation to evaluate resonance parameters from several experimental data sets. A Monte Carlo approach was used for resonance spin assignments and generating 59 small fictitious resonance levels which were shown to improve the cumulative level, Porter-Thomas, and Wigner distributions as compared to theoretical predictions. Covariance information was also generated for the entire resolved resonance region. Finally, the positive impact of the new evaluation was validated through benchmark calculations which were sensitive to the 181 Ta cross section and showed improvement in the reactivity bias for several benchmark cases.
The Zeus experiments with lead (Pb) were a series of measurements performed at the National Criticality Experiments Research Center (NCERC) in collaboration with the Japan Atomic Energy Agency (JAEA). Personnel from the JAEA who assisted with the experiment were Masahiro Fukushima and Akito Oizumi. The measurements were performed by Joetta Goda, Geordie McKenzie, John Bounds, Jessie Walker, Travis Grove, Theresa Cutler, Rene Sanchez, and Jesson Hutchinson from Los Alamos National Laboratory (LANL). The purpose of these experiments was to validate Pb nuclear cross sections and Pb void reactivity worth using the Comet critical assembly machine. Plates of highly enriched uranium (HEU) and Pb were arranged in a cylindrical configuration with full copper (Cu) reflection. To study the Pb void reactivity worth, a varying number of cylindrical aluminum (Al) spacers with voids replaced Pb plates in different configurations. Four configurations, which used zero to eight Al spacers, were evaluated as benchmarks.
Presentation Hosted at Device Assembly Facility (DAF). Joint collaboration by Atomic Weapons Establishment (AWE) and Lawrence Livermore National Laboratory (LLNL). Multiple measurements were recorded through a two-week period with 12 unique objects measured. LLNL deployed Machine learning software program for diagnostic assessments. Current status notes the dedicated DAF team LLNL maintains. Additionally, LLNL is compiling a report on the AWE-LLNL measurements and designing security benchmark experiments. The presentation concludes with future work envisioned.
This report addresses the requirements of Milestone M3.4 AI capability to identify and predict maintenance events. Development of digital twins (DT) for molten salt reactor (MSR) components is crucial for reducing operating and maintenance costs (O&M) and ensuring commercial viability of these reactors. Our focus is on development of DT for MSR primary system heat exchanger (HX), a critical component, the fault in which can reduce operating efficiency and force reactor shutdown. We are investigating the feasibility of a conceptual DT of HX consisting of internal distributed temperature sensing with fiber optics and machine learning (ML) algorithms to detect and localize faults. To determine the optimal approach to detection and localization of channel plugging, we benchmark seven different ML models: Logistic Regression, K-Nearest Neighbors (KNN), Gaussian Naïve Bayes, Support Vector Machines (SVM), Decision Tree Classifier, Random Forest Tree Classifier, and Feed-Forward Neural Network. ML algorithms are benchmarked using synthetic HX plugging data generated with computational fluid dynamics COMSOL software, with added brown noise to represent experimental noise. We show that the best performance is obtained with the Decision Tree classifier.
NASA's largest new start development program is the Orbital Space Plane (OSP) Program. The program is currently in the formulation stage. One of the critical issues to be resolved, prior to initiating full-scale development, is establishing cost credibility of NASA s budget estimates for development, production, and operations of the OSP. This paper will discuss the processes, tools, and methodologies that NASA, along with its industry partners, are implementing to assure cost credibility for the OSP program. Results of benchmarking of current tools and the development of new cost estimating capabilities and approaches will be discussed.