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At least 1,333 records · Page 74

Continuous Integration Service at Fermilab

This paper describes the current architecture of Continuous Integration (CI) service developed at Fermilab, encountered successes and difficulties, as well as future development plans. The current experiment code has hundreds of contributors that provide new features, bug fixes, and other improvements. Version control systems help developers to collaborate in contributing software for their experiments, while the CI system helps developers keep their code healthy. The Fermilab CI service allows experiments and projects to test and validate their offline production and analysis code on the supported platforms. It is built on top of Jenkins, designed to be set up from a configuration file that provides implementation for each phase of the CI workflow, and able to validate experiment code through grid jobs. This CI service provides a dashboard for easy access to logs and statistical graphs. Since the CI service has been adopted by Fermilab experiments/projects, it proved to be very useful to intercept issues in their code early on and get them fixed before running it in production. Currently the CI service is in use by the ArgoNeuT, DUNE, g-2, LArIAT, MINERvA, mu2e, NOvA, SBND and uBooNE experiments and by the following projects: ART and LArSoft software suites, GENIE, and Glidein-WMS. The CI service is under active development and planning to support code profiling.

Di benedetto, Vito↗

Machine learning guided selection of broad-spectrum epitope-specific functional antibodies for "Disease X"

Our project established and demonstrated a transfer learning framework that enables prediction of antibody–antigen interactions across related viruses. The approach focused on three major activities: 1. Conserved region and epitope identification – We compared viral protein structures and sequences to identify shared receptor-binding domains and neutralizing epitope regions across variants and related viruses. These conserved features formed the foundation for discovering broadly functional antibodies. 2. Machine learning model development – We built neural network–based models that integrate epitope features with antibody sequence information. Instead of relying solely on structural or physical properties, the models learned transferable patterns that describe antibody binding potential across different viral families. 3. Transfer learning and validation – Using SARS-CoV-2 and Ebola as source systems, we successfully transferred learned epitope features to predict antibody interactions for SARS CoV-1 and Marburg virus. Iterative cycles of dataset generation, retraining, and evaluation improved generalization and predictive power, ensuring the framework can adapt to new threats.

59 BASIC BIOLOGICAL SCIENCES↗

Development history of the Hybrid Test Vehicle

Phase I of a joint Department of Energy/Jet Propulsion Laboratory Program undertook the development of the Hybrid Test Vehicle (HTV), which has subsequently progressed through design, fabrication, and testing and evaluation phases. Attention is presently given to the design and test experience gained during the HTV development program, and a discussion is presented of the design features and performance capabilities of the various 'mule' vehicles, devoted to the separate development of engine microprocessor control, vehicle structure, and mechanical components, whose elements were incorporated into the final HTV design. Computer projections of the HTV's performance are given.

Trummel, M. C.↗

Revisiting the Interpretation of Thorium Abundances at Hansteen Alpha

Hansteen Alpha is one of the few remaining locations on the Moon thought to be formed by highlands volcanism. Hansteen Alpha is a triangular shaped feature located in the southern portion of Oceanus Procellarum (12 degrees W, 50 degrees S) and its size is approximately 25 km on each side. As described by Hawke et al., there is clear evidence that: 1) Hansteen Alpha was emplaced by extrusive volcanic processes; and 2) it was formed by a viscous lava that should be enriched in Th. However, in the study of Hawke et al. using available Lunar Prospector (LP) Th data, it was concluded that the Hansteen Alpha region was not greatly enriched in Th as would be expected for a highly evolved, viscous lava. It was further concluded based on other compositional data that the magma that formed Hansteen Alpha did not correspond to any known rock type. Here we revisit the interpretation of Th abundances at Hansteen Alpha for a couple of reasons. First, the size of Hansteen Alpha is smaller than the spatial resolution of the LP Gamma-ray Spectrometer (LP-GRS) from which the Th abundances were derived. Therefore, the LP-GRS pixels covering Hansteen Alpha may not truly represent the Th abundance of the Hansteen Alpha feature. Second, recent work has led to a much greater understanding of the Th spatial distribution for small-area features on the lunar surface. In particular, using forward modeling techniques, we have developed the ability to obtain information about Th abundances for features that are at or smaller than the FWHM spatial resolution (approximately [80 square kilometers]) of the LP-GRS data.

Lawrence, D. J.↗

Interpretable Machine Learning for Molecular Biosignatures: a Novel Single-Sample Feature Importance Method That Is Sensitive To Statistical Interactions

Isotope ratio mass spectrometry (IRMS) of volatiles (e.g., CO 2 ) promises to be a powerful tool for potential biosignature detection for future missions to ocean worlds (OW) such as Europa and Enceladus. Machine learning (ML) methods for IRMS data could enable science autonomy by onboard prediction of seawater chemistry and biosignature presence. However, ML models are likely to be complex and involve statistical interactions between features (variables), which can make predictions seem opaque and enigmatic. For ML predictions as significant as extraterrestrial biosignatures, we must place extraordinary confidence in models. It is therefore essential that these models make interpretable predictions (i.e., human-understandable) and include false-prediction diagnostics. We achieve high accuracy and interpretability in ML biosignature and seawater chemistry models for OW through a nearest-neighbors feature selection tool that detects statistical interactions between predictors, constructs interaction networks for visualization of selected features working together to make a prediction, and reports single-sample feature importance scores for false-detection diagnostics. Here we develop a novel single-sample nearest-neighbors projected distance regression(ssNPDR) feature selection method that improves upon existing single-sample algorithms through the inclusion of statistical interactions while providing false-prediction diagnostics for ML models.

geochemistry↗

Microscopic Disease Extension in Three Dimensions for Non-Small-Cell Lung Cancer: Development of a Prediction Model Using Pathology-Validated Positron Emission Tomography and Computed Tomography Features

Purpose: One major uncertainty in radiotherapy planning of non-small-cell lung cancer concerns the definition of the clinical target volume (CTV), meant to cover potential microscopic disease extension (MDE) around the macroscopically visible tumor. The primary aim of this study was to establish pretreatment risk factors for the presence of MDE. The secondary aim was to establish the impact of these factors on the accuracy of positron emission tomography (PET) and computed tomography (CT) to assess the total tumor-bearing region at pathologic examination (CTV{sub path}). Methods and Materials: 34 patients with non-small-cell lung cancer who underwent CT and PET before lobectomy were included. Specimens were examined microscopically for MDE. The gross tumor volume (GTV) on CT and PET (GTV{sub CT} and GTV{sub PET}, respectively) was compared with the GTV and the CTV at pathologic examination, tissue deformations being taken into account. Using multivariate logistic regression, image-based risk factors for the presence of MDE were identified, and a prediction model was developed based on these factors. Results: MDE was found in 17 of 34 patients (50%). The MDE did not exceed 26 mm in 90% of patients. In multivariate analysis, two parameters (mean CT tumor density and GTV{sub CT}) were significantly associated with MDE. The area under the curve of the two-parameter prediction model was 0.86. Thirteen tumors (38%, 95% CI: 24-55%) were identified as low risk for MDE, being potential candidates for reduced-intensity therapy around the GTV. In the low-risk group, the effective diameter of the GTV{sub CT/PET} accurately represented the CTV{sub path}. In the high-risk group, GTV{sub CT/PET} underestimated the CTV{sub path} with, on average, 19.2 and 26.7 mm, respectively. Conclusions: CT features have potential to predict the presence of MDE. Tumors identified as low risk of MDE show lower rates of disease around the GTV than do high-risk tumors. Both CT and PET accurately visualize the CTV{sub path} in low-risk tumors but underestimate it in high-risk tumors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SOT: A rapid prototype using TAE windows

The development of the window interface extension feature of the Transportable Applications Executive (TAE) is discussed. This feature is being used to prototype a space station payload interface in order to demonstrate and assess the benefits of using windows on a bit mapped display and also to convey the concept of telescience, the control and operation of space station payloads from remote sites. The prototype version of the TAE with windows operates on a DEC VAXstation 100. This workstation has a high resolution 19 inch bit mapped display, a keyboard and a three-button mouse. The VAXstation 100 is not a stand-alone workstation, but is controlled by software executing on a VAX/8600. A short scenario was developed utilizing the Solar Optical Telescope (SOT) as an example payload. In the scenario the end-user station includes the VAXstation 100 plus an image analysis terminal used to display the CCD images. The layout and use of the prototype elements, i.e., the root menu, payload status window, and target acquisition menu is described.

Stephens, Mark↗

Guidelines for Safe, High Performing Li-Ion Battery Designs for Manned Vehicles

New design features and test methods are in development at NASA to take advantage of the newest high power and energy dense commercial Li-ion cell designs and to achieve passively thermal runaway (TR) propagation resistant (PPR) designs for manned missions requiring high power/voltage. The goal is to minimize the parasitic mass and volume of the battery components; thus reaching a balance between high battery specific power (W/kg) and energy (Wh/kg) as well as power (W/L) and energy density (Wh/L). Current 18650 cell designs achieve greater than 275 Wh/kg, greater than 725 Wh/L, but present high risks of side wall breaching during TR which can defeat many other safety features resulting in nearly immediate TR propagation. This work seeks to better understand the phenomena of cell side wall breaches and to determine the effectiveness of promising battery design features for achieving safe, high performing battery designs for high voltage/power applications.

Darst, John J.↗

Driving Design Factors for Safe, High Power Batteries for Space Applications

Final Document is attached. New design features and test methods are in development at NASA to take advantage of the newest high power and energy dense commercial Li-ion cell designs and to achieve passively thermal runaway (TR) propagation resistant (PPR) designs for manned missions requiring high power/voltage. The goal is to minimize the parasitic mass and volume of the battery components; thus reaching a balance between high battery specific power (W/kg) and energy (Wh/kg) as well as power (W/L) and energy density (Wh/L). Current 18650 cell designs achieve greater than 275 Wh/kg, greater than 725 Wh/L, but present high risks of side wall breaching during TR which can defeat many other safety features resulting in nearly immediate TR propagation. This work seeks to better understand the phenomena of cell side wall breaches and to determine the effectiveness of promising battery design features for achieving safe, high performing battery designs for high voltage/power applications.

Li-ion↗

Modeling of HVAC operational faults in building performance simulation

Operational faults are common in the heating, ventilating, and air conditioning (HVAC) systems of existing buildings, leading to a decrease in energy efficiency and occupant comfort. Various fault detection and diagnostic methods have been developed to identify and analyze HVAC operational faults at the component or subsystem level. However, current methods lack a holistic approach to predicting the overall impacts of faults at the building level—an approach that adequately addresses the coupling between various operational components, the synchronized effect between simultaneous faults, and the dynamic nature of fault severity. This study introduces the novel development of a fault-modeling feature in EnergyPlus which fills in the knowledge gap left by previous studies. This paper presents the design and implementation of the new feature in EnergyPlus and discusses in detail the fault-modeling challenges faced. The new fault-modeling feature enables EnergyPlus to quantify the impacts of faults on building energy use and occupant comfort, thus supporting the decision making of timely fault corrections. Including actual building operational faults in energy models also improves the accuracy of the baseline model, which is critical in the measurement and verification of retrofit or commissioning projects. As an example, EnergyPlus version 8.6 was used to investigate the impacts of a number of typical operational faults in an office building across several U.S. climate zones. Finally, the results demonstrate that the faults have significant impacts on building energy performance as well as on occupant thermal comfort. Finally, the paper introduces future development plans for EnergyPlus fault-modeling capability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

ECP SOLLVE: Validation and Verification Testsuite Status Update and Compiler Insight for OpenMP

The OpenMP language continues to evolve with every new specification release, as does the need to validate and verify the new features that have been implemented by the different vendors. With the release of OpenMP 5.0 and OpenMP 5.1, new target offload and host-based features have been introduced to the programming model. While OpenMP continues to grow in maturity, there is an observable growth in the number of compiler and hardware vendors that support OpenMP. In this manuscript, the main focus is on evaluating the conformity and OpenMP implementation progress of various compiler vendors such as Cray, IBM, GNU, Clang/LLVM, NVIDIA, and Intel. More specifically, the 4.5, 5.0, and 5.1 versions of the OpenMP specification are analyzed. For our experimental setup, the Crusher and Summit computing systems hosted by Oak Ridge National Lab’s Computing Facilities are utilized. The effort of vendor agnostic analysis of these implementations is especially valuable for application developers who are using new OpenMP features to accelerate their scientific codes. Insights are presented into the current implementation status of various vendors, the progression of specific compiler’s support for OpenMP overtime, the subset of OpenMP 4.5, 5.0, and 5.1 that is supported by all compilers, and examples of how our test suite has influenced discussion regarding the correct interpretation of the OpenMP specification. By evaluating OpenMP conformity of pre-Exascale computing systems, the aim is to detail progress and status of AMD + Cray ecosystem before the system and their OpenMP implementation is used for mission critical applications when the first Exascale Computer Frontier is made available to applications.

Huber, Thomas↗

Feature extraction applied to agricultural crops as seen by LANDSAT

The physical interpretation of the spectral-temporal structure of LANDSAT data can be conveniently described in terms of a graphic descriptive model called the Tassled Cap. This model has been a source of development not only in crop-related feature extraction, but also for data screening and for haze effects correction. Following its qualitative description and an indication of its applications, the model is used to analyze several feature extraction algorithms.

Kauth, R. J.↗

Computational epidemiological tools for pandemic analysis, understanding, and response

This suite of software tools is being developed to enhance and analyze computational epidemiological models that incorporate realistic disease dynamics and human behavior, with the goal of supporting epidemic and pandemic response. Specifically, the tools enable data analysis, feature extraction, data synthesis, machine learning model development, and prediction of key public health outcomes, such as cases, hospitalizations, deaths, and behavioral responses, for airborne infectious diseases like COVID-19 and influenza.

Butts, David↗

Development of a Deployable Nonmetallic Boom for Reconfigurable Systems of Small Spacecraft

In 2005, NASA commenced Phase 1 of the Modular Reconfigurable High Energy Technology Demonstrator (MRHE) program to investigate reconfigurable systems of small spacecraft. During that year, Lockheed Martin's Advanced Technology Center (ATC) led an accelerated effort to develop a 1-g MRHE concept demonstration featuring robotic spacecraft simulators equipped with docking mechanisms and deployable booms. The deployable boom built for MRHE was the result of a joint effort in which ATK was primarily responsible for developing and fabricating the Collapsible Rollable Tube (CRT patent pending) boom while Lockheed Martin designed and built the motorized Boom Deployment Mechanism (BDM) under a concurrent but separate IR&D program. Tight coordination was necessary to meet testbed integration and functionality requirements. This paper provides an overview of the CRT boom and BDM designs and presents preliminary results of integration and testing to support the MRHE demonstration.

Rehnmark, Fredrik↗

Distributed Embedded Energy Converters for Ocean Wave Energy Harvesting: Enabling a Domain of Transformative Technologies: Preprint

Distributed embedded energy conversion technology (DEEC-Tec) is a very promising - but underdeveloped - domain in marine renewable energy research. The technology utilizes small distributed embedded energy converters (DEECs) that, in aggregate, form a much larger energy harvesting-converting structure. Each DEEC is a small transducer - an individual mechanism that converts one form of energy into another. A transducer's specific mode of operation can be based upon any number of physical phenomena, including variable capacitance, variable magnetic fields, or piezoelectrics. It is the dynamic deformation of a structure made from such DEECs (a DEEC-Tec structure) that provides the needed physical phenomena (the external energy source) for the underlying transducers to intake and convert energy into another form, such as electricity. DEEC-Tec structures designed specifically to dynamically deform in the presence of ocean wave energy - for the purpose of harvesting and converting that energy - can be called flexWECs. A flexWEC's gross shape (topology) and its compliant characteristics (morphologies) are chiefly determined by how the DEECs making up its structure are arranged and implemented. In turn, those corresponding topologies and morphologies will largely determine how a flexWEC interacts with - and dynamically deforms within - the presence of ocean wave energy. FlexWECs appear to have many attractive features, including broad-banded ocean energy conversion, in situ energy conversion throughout an entire flexWEC structure, inherent redundancy, and appealing material and manufacturing costs. To this end, the design and development of any particular flexWEC or flexWEC feature is a revolutionary opportunity for how we conceptualize and envision the future of ocean wave energy conversion.

50 EE - Wind and Water Power Program - Water (EE-4↗

Distributed Embedded Energy Converters for Ocean Wave Energy Harvesting: Enabling a Domain of Transformative Flexible Technologies

Distributed embedded energy conversion technology (DEEC-Tec) is a very promising - but underdeveloped - domain in marine renewable energy research. The technology utilizes small distributed embedded energy converters (DEECs) that, in aggregate, form a much larger energy harvesting-converting structure. Each DEEC is a small transducer - an individual mechanism that converts one form of energy into another. A transducer's specific mode of operation can be based upon any number of physical phenomena, including variable capacitance, variable magnetic fields, or piezoelectrics. It is the dynamic deformation of a structure made from such DEECs (a DEEC-Tec structure) that provides the needed physical phenomena (the external energy source) for the underlying transducers to intake and convert energy into another form, such as electricity. DEEC-Tec structures designed specifically to dynamically deform in the presence of ocean wave energy - for the purpose of harvesting and converting that energy - can be called flexWECs. A flexWEC's gross shape (topology) and its compliant characteristics (morphologies) are chiefly determined by how the DEECs making up its structure are arranged and implemented. In turn, those corresponding topologies and morphologies will largely determine how a flexWEC interacts with - and dynamically deforms within - the presence of ocean wave energy. FlexWECs appear to have many attractive features, including broad-banded ocean energy conversion, in situ energy conversion throughout an entire flexWEC structure, inherent redundancy, and appealing material and manufacturing costs. To this end, the design and development of any particular flexWEC or flexWEC feature is a revolutionary opportunity for how we conceptualize and envision the future of ocean wave energy conversion.

DEEC↗

IAEA CONNECT: Connecting the network of networks for enhanced communication and training - 15143

To further support the exchange of information and cooperation in the management of radioactive waste, decommissioning and environmental remediation, a new tool has been developed and was officially launched in October 2014: The IAEA CONNECT platform. This paper describes the platform, including its objectives, principles, participation/audience, methods of work, Governance document, current available networks and features, and explains the context it was developed in, as well as the reasons behind its creation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Development of safety requirements for HTGRs design - 18467

The safety requirements for the design of High Temperature Gas-cooled Reactors (HTGRs), which is analogous to the IAEA specific safety requirements (SSR) for Light Water Reactor (LWR) design (IAEA SSR-2/1), has been developed by the research committee established in the Atomic Energy Society of Japan so as to incorporate the HTGR safety features demonstrated by High Temperature Engineering Test Reactor (HTTR), lessons learned from the accident of Fukushima Daiichi Nuclear Power Station and requirements for the coupling of the hydrogen production plants with nuclear plant. The safety design approach was determined to establish a high level of safety design standards by utilizing inherent safety features of HTGRs. The safety requirements is then developed using the objectives provisions tree methodology based on the safety design approach. The requirements for a structural integrity of fuel during accident conditions, for a confinement structure instead of a leak-tight pressure resistance containment vessel, for a passive residual heat removal from outside of reactor pressure vessel, etc., which are significantly different from those of LWR, are stated in the developed safety requirements. This paper describes overview of the proposed HTGR specific safety requirements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗