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At least 757 records · Page 42

Effects of Chlorine Capture and a Proposed Density Law on the Reactivity of Plutonium Solution Systems

During fissionable material processing, all normal and credible abnormal conditions must remain safely subcritical. Nuclear Criticality Safety (NCS) uses a number of methods to determine subcriticality, one of which is the use of neutron transport codes such as MCNP6. In order to create models for use with MCNP6, both the geometry and materials in fissionable material processes must be known, or assumptions must be made and quantified for the impact to bias. One of the systems with a significant amount of bias due to material modeling assumptions is in the area of aqueous plutonium processing. These solutions are typically plutonium nitrate solutions or plutonium chloride solutions, which are modeled as fictitious plutonium metal-water mixtures because little is known about the actual density of the solution and there is no current predictive capability approved for use at Los Alamos National Laboratory (LANL) for modeling them. This research is currently underway to fill the gap and develop an algorithm for use with MCNP6 to model the density of plutonium chloride solutions. The method is to be validated with experimental data for density, and also validated with critical experiments using MCNP6. Note that the Chlorine Worth Study (CWS) was performed in December 2021 to help bridge the gap in chlorine data for critical experiments, and is currently awaiting International Criticality Safety Benchmark Evaluation Project (ICSBEP) review. This study was performed by LANL at the National Criticality Experiments Research Center (NCERC) at the Nevada National Security Site (NNSS). Additional information regarding this experiment may currently be found in LA-UR- 22-29180. Additionally, the Chemistry-Actinide Analytical Chemistry (C-AAC) at LANL has performed a number of solution density measurements for PuCl 3 -HC 1 -H 2 O, allowing for such data be used to create a semi-empirical density via the Pitzer method. The published dataset for the measurements is documented in LA-UR-22-25454. This method has already been tested successfully for aqueous plutonium nitrate solutions in SCALE. Current solution density measurements exist of plutonium concentrations of 0-~142g/L, all at 2M HC1, at temperatures 20-40°C. Additional data was taken for HC1-corrected density values, which essentially mimics the data for a pure PuCl x -water solution. The calculations in this report aim to support the current research by demonstrating the difference in system reactivity for the current modeling method when compared to the new proposed modeling with a density law implementation, which is being written as a Python tool to be used with MCNP6.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

VA Determinants of Health Data Curation Documentation FY25-Q2

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Determinants of Health (EDH) project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1km grid) to another (e.g., US Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, US Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1km grids. Some economic data may only be available at the zip code level. In this context, ‘standardized’ means that all datasets share the same spatial extent (e.g., US Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

97 MATHEMATICS AND COMPUTING↗

VA Determinants of Health Data Curation Documentation FY25-Q3

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Determinants of Health (EDH) project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1km grid) to another (e.g., US Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, US Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1km grids. Some economic data may only be available at the zip code level. In this context, ‘standardized’ means that all datasets share the same spatial extent (e.g., US Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

97 MATHEMATICS AND COMPUTING↗

VA Community Determinants of Health Data Curation Documentation FY25-Q4

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Determinants of Health (EDH) project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1km grid) to another (e.g., US Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, US Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1km grids. Some economic data may only be available at the zip code level. In this context, standardized’ means that all datasets share the same spatial extent (e.g., US Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

97 MATHEMATICS AND COMPUTING↗

VA Community Determinants of Health Data Curation Documentation FY26-Q1

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Community Determinants of Health (EDH) Data project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1km grid) to another (e.g., US Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, US Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1km grids. Some economic data may only be available at the zip code level. In this context, ‘standardized’ means that all datasets share the same spatial extent (e.g., US Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Community Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

99 GENERAL AND MISCELLANEOUS↗

Countering Weapons of Mass Destruction (CWMD) Zero Trust Framework: CWMD Zero Trust Principles Model

The research focuses on the critical need for enhanced cybersecurity within the Countering Weapons of Mass Destruction (CWMD) Office, specifically targeting Chemical, Biological, Radiological, and Nuclear devices. Traditional perimeter-based security models are insufficient against modern cyber threats, prompting a shift toward Zero Trust principles (ZTP) that emphasize continuous verification and stringent security for all devices. Federal directives mandate the adoption of Zero Trust (ZT) across agencies, supported by guidelines from National Institute of Standards and Technology (NIST), U.S. Department of Homeland Security (DHS) Cybersecurity and Infrastructure Security Agency (CISA), U.S. Department of Defense (DoD) and National Security Agency (NSA). The research involved mapping ZT guidance from these agencies to develop tailored CWMD ZTP. The study identified gaps and areas for improvement, including clear transitional guidance from traditional to ZT architectures and the focus on explicit cross cutting capabilities. Design improvements are recommended to ensure increased comprehensive protection and resilience against sophisticated cyber threats for Chemical, Biological, Radiological, and Nuclear (CBRN) devices. Collaborative efforts among federal agencies are essential for the successful deployment of an optimized ZT guidance.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

VA Community Determinants of Health Data Curation Documentation FY26-Q2

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Community Determinants of Health (EDH) Data project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1 km grid) to another (e.g., U.S. Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, U.S. Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1 km grids. Some economic data may only be available at the ZIP code level. In this context, ‘standardized’ means that all datasets share the same spatial extent (e.g., U.S. Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Community Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

99 GENERAL AND MISCELLANEOUS↗

Studies of Model Immiscible Systems

The objectives are to use model transparent monotectics to obtain fundamental information applicable to two-phase systems in general, to apply this understanding to materials of interest in the Microgravity Science and Applications program, and to interpret results of flight experimental involving monotectic alloys. A number of model immiscible systems are in use to study various aspects of two-phase behavior within the miscibility gap and during solidification. Particle growth, coalescence and particle motions are under investigation using a holographic microscopy system. The system is capable of working with particle densities up to 10 to the 7th power particles/cubic centimeters through a 100 micron depth and can resolve particles of the order of 2 to 3 micron in diameter throughout the entire cell volume. Particle size, distribution changes with respect to time and temperature are observable from sequential holograms. Initial experiments using diethylene glycol/ethyl salicylate (DEG/ES) have demonstrated the usefulness of the technique. The thermal system controls temperature to at least plus or minus 0.001 K over the course of an experiment. A time-lapse film, made from holograms, of a succinonitrile/water solution shows particle size and number distribution changes with time under isothermal conditions. The observations are consistent with Ostwald ripening theory.

Frazier, D. O.↗

SSME HPFTP/AT Turbine Blade Platform Featherseal Damper Design

During the Space Shuttle Main Engines (SSM) HPFtP/AT development program, engine hot fire testing resulted in turbine blade fatigue cracks. The cracks were noted after only a few tests and a several hundred seconds versus the design goal of 60 tests and >30,000 seconds. Subsequent investigation attributed the distress to excessive steady and dynamic loads. To address these excessive turbine blade loads, Pratt & Whitney Liquid Space Propulsion engineers designed and developed retrofitable turbine blade to blade platform featherseal dampers. Since incorporation of these dampers, along with other turbine blade system improvements, there has been no observed SSME HPFTP/AT turbine blade fatigue cracking. The high time HPFTP/AT blade now has accumulated 32 starts and 19,200 seconds hot fire test time. Figure #1 illustrates the HPFTP/AT turbine blade platform featherseal dampers. The approached selected was to improve the turbine blade structural capability while simultaneously reducing loads. To achieve this goal, the featherseal dampers were designed to seal the blade to blade platform gap and damp the dynamic motions. Sealing improves the steady stress margins by increasing turbine efficiency and improving turbine blade attachment thermal conditioning. Load reduction was achieved through damping. Thin Haynes 188 sheet metal was selected based on its material properties (hydrogen resistance, elongation, tensile strengths, etc.). The 36,000 rpm wheel speed of the rotor result in a normal load of 120#/blade. The featherseals then act as micro-slip dampers during actual SSME operation. After initial design and analysis (prior to full engine testing), the featherseal dampers were tested in P&W's spin rig facility in West Palm Beach, Florida. Both dynamic strain gages and turbine blade tip displacement measurements were utilized to quantify the featherseal damper effectiveness. Full speed (36,000 rpm), room temperature rig testing verified the elimination of fundamental mode (i.e, modes 1 & 2) resonant response. The reduction in turbine blade dynamic response is shown for a typical turbine blade. This paper discusses the design and verification of these dampers. The numerous benefits associated with this design concept warrants consideration in existing and future turbomachinery applications.

Montgomery, S. K.↗

Test Plan for a Calibration Demonstration System for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change. One of the major objectives of CLARREO is to advance the accuracy of SI traceable absolute calibration at infrared and reflected solar wavelengths. This advance is required to reach the on-orbit absolute accuracy required to allow climate change observations to survive data gaps while remaining sufficiently accurate to observe climate change to within the uncertainty of the limit of natural variability. While these capabilities exist at NIST in the laboratory, there is a need to demonstrate that it can move successfully from NIST to NASA and/or instrument vendor capabilities for future spaceborne instruments. The current work describes the test plan for the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. The goal of the CDS is to allow the testing and evaluation of calibration approaches , alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result of efforts with the SOLARIS CDS will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections. The CLARREO mission addresses the need to observe high-accuracy, long-term climate change trends and advance the accuracy of SI traceable absolute calibration. The current work describes the test plan for the SOLARIS which is the calibration demonstration system for the reflected solar portion of CLARREO. SOLARIS provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections.

Thome, Kurtis↗

Risk of Crew Adverse Health Event Due to Altered Immune Response

Determining the effect of space travel on the human immune system has proven to be extremely challenging. Limited opportunities for in-flight studies, varying mission durations, technical and logistical obstacles, small subject numbers, and a broad range of potential assays have contributed to this problem. Additionally, the inherent complexity of the immune system, with its vast array of cell populations, sub-populations, diverse regulatory molecules, and broad interactions with other physiological systems, makes determining precise variables to measure very difficult. There is also the challenge of determining the clinical significance of any observed immune alterations. Will such a change lead to disease, or is it a transient subclinical observation related to short-term stress? The effect of this problem may be observed by scanning publications associated with immunity and spaceflight, which began to appear during the 1970s. Although individually they are each valid studies, the comprehensive literature to date suffers from widely varying sampling methods and assay techniques, low subject counts, and sometimes a disparate focus on narrow aspects of immunity. The most clinically relevant data are derived from in-flight human studies, which have demonstrated altered cell-mediated immunity and reactivation of latent herpes viruses. Much more data are available from post-flight testing of humans, with clear evidence of altered cytokine production patterns, altered leukocyte distribution, continued latent viral reactivation, and evidence of dramatically altered virus-specific immunity. It is unknown if post-flight assessments relate to the in-flight condition or are a response to landing stress and readaptation. In-flight culture of cells has clearly demonstrated that immune cells are gravity-sensitive and display altered functional characteristics. It is unknown if these data are related to in vivo immune cell function or are an artifact of microgravity culture. Ground analog testing of humans and animals, as well as microgravity-analog cell culture, has demonstrated utility. However, in all cases, it is not known with certainty if these data would reflect similar testing during space travel. Given their ready availability, ground analogs may be extremely useful for assay development and the evaluation of potential countermeasures. In general, the evidence base suffers from widely disparate studies on small numbers of subjects that do not directly correlate well with each other or spaceflight itself. Also lacking are investigations of the effect of gender on adaption to spaceflight. This results in significant knowledge 'gaps' that must be filled by future studies to completely determine any clinical risk related to immunity for human exploration-class space missions. These gaps include a significant lack of in-flight data, particularly during long-duration space missions. The International Space Station represents an excellent science platform with which to address this knowledge gap. Other knowledge gaps include lack of a single validated ground analog for the phenomenon and a lack of flight-compatible laboratory equipment capable of monitoring astronauts (for either clinical or research purposes). However, enough significant data exist, as described in this manuscript, to warrant addressing this phenomenon during the utilization phase of the ISS. A recent Space Shuttle investigation has confirmed the 31 in-flight nature of immune dysregulation, demonstrating that it is not merely a post-flight phenomenon. Several current studies are ongoing onboard the ISS that should thoroughly characterize the phenomenon. NASA recognizes that if spaceflight-associated immune dysregulation persists during exploration flights in conjunction with other dangers, such as high-energy radiation, the result may be a significant clinical risk. This emphasizes the need for a continued integrated comprehensive approach to determining the effect of prolonged spaceflight, separated from transient launch and landing stresses, on human immunity. After such studies, the phenomenon will be understood, and, hopefully, a monitoring strategy will have been developed that could be used to monitor the effectiveness of countermeasure

Crucian, Brian↗

Exploration Systems Exterior Lighting Design Guidance

Humans are returning to the Moon — this time, to stay. NASA has selected a location that maximizes line-of-sight communication with Earth, solar visibility, and access to water ice: the Lunar South Pole (LSP). While the Sun is more consistently in the lunar sky at the poles, it never rises more than 7° above the horizon in the target landing regions. This harsh lighting environment--never experienced during the Apollo missions or in human spaceflight--presents an engineering challenge: Support and protect functional vision. The human vision system, which despite having a high-dynamic range, cannot see well into bright light and cannot adapt quickly from bright to dark or vice versa. The design of helmets, windows, and lighting solutions must work in a complementary fashion to achieve a system of lighting and functional vision support that enables crews to see into darkness while their eyes are light-adapted and see in bright light while still dark-adapted that protects their eyes from injury. This report brings together information and identifies gaps related to LSP Natural environment (topology, regolith, temperature, lighting, and so forth), NASA historical experience exploring the Moon, human vision capabilities and needs, exploration operations, simulation capabilities and needs (for design verification, training, mission planning, and so forth) and existing engineering, safety, medical and performance requirements related to support human exploration.

Simulation↗

Mads.jl

Mads.jl (Model analysis and decision support in Julia) is a code that streamlines the process of using data and models for analysis and decision support. It is based on another open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11- 035). Mads.jl can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. It enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. The code also can use a series of alternative adaptive computational techniques for Bayesian sampling, Monte Carlo, and Bayesian Information-Gap Decision Theory. The code is implemented in the Julia programming language, and has high-performance (parallel) and memory management capabilities. The code uses a series of third party modules developed by others. The code development will also include contributions to the existing third party modules written in Julia; this contributions will be important for the efficient implementation of the algorithm used by Mads.jl. The code also uses a series of LANL developed modules that are developed by Dan O'Malley; these modules will be also a part of the Mads.jl release. Mads.jl will be released under GPL V3 license. The code will be distributed as a Git repo at gitlab.com and github.com. Mads.jl manual and documentation will be posted at madsjulia.lanl.gov.

Vesselinov, Velimir↗

A Mechanistic Source Term Calculation for a Metal Fuel Sodium Fast Reactor

A mechanistic source term (MST) calculation attempts to realistically assess the transport and release of radionuclides from a reactor system to the environment during a specific accident sequence. The U.S. Nuclear Regulatory Commission (NRC) has repeatedly stated its expectation that advanced reactor vendors will utilize an MST during the U.S. reactor licensing process. As part of a project to examine possible impediments to sodium fast reactor (SFR) licensing in the U.S., an analysis was conducted regarding the current capabilities to perform an MST for a metal fuel SFR. The purpose of the project was to identify and prioritize any gaps in current computational tools, and the associated database, for the accurate assessment of an MST. The results of the study demonstrate that an SFR MST is possible with current tools and data, but several gaps exist that may lead to possibly unacceptable levels of uncertainty, depending on the goals of the MST analysis.

Grabaskas, David↗

IceCube: Demonstration of an 883 GHz Radiometer for Ice Cloud Remote Sensing

IceCube was a technology demonstration of an 883 GHz heterodyne radiometer on a 3U CubeSat for ice cloud characterization. The project was a collaboration between Goddard Space Flight Center, Virginia Diodes Inc., and Wallops Flight Facility. IceCube was launched to the International Space Station (ISS) in April 2017, and was deployed to the orbit in May 2017. The radiometer measured ice cloud emissions from an ISS orbit for over 15 months. IceCube generated the first 883 GHz cloud map over a large operation temperature range of (5 ºC—37 ºC). Cloud ice plays a major role in the cloud precipitation process and Earth’s energy budget. Ice clouds are used in global circulation models as tuning parameters to achieve model agreement with observation at the top of the atmosphere in the radiation budget and at the bottom for precipitation, however, due to a lack of accurate ice cloud measurements large uncertainties exist in these models. Submillimeter wave remote sensing is capable of addressing this issue by measuring cloud ice mass and microphysical properties in the middle-to-upper troposphere. This fills the sensitivity gap not covered by the visible/infrared and microwave sensors [1]. The goal of IceCube was to increase the TRL of a heterodyne 883 GHz radiometer (using commercial parts) from 5 to 7 by validating the performance in a relevant spaceflight environment. The design of the radiometer was driven by frequency of operation, bandwidth, calibration, available power, and thermal environment requirements. The design included a 15 mm aperture off-axis parabolic reflector with a Potter feed horn, an 883 GHz 2nd-harmonic mixer that is fed by a local oscillator chain with a 24.3 GHz dielectric resonator (MLA), followed by a 6 GHz bandwidth centered at 9 GHz intermediate frequency assembly (IFA), receiver interface card, and power distribution unit. The IFA included an internal noise diode calibration to separate the MLA performance from the rest of the system. For this the radiometer had four operational states: antenna, antenna + noise, reference, and reference + noise; each state’s duration was 10 ms. The total power dissipation of the instrument was 5.6 W. The spacecraft had spinning capabilities to provide a cold sky view for calibration. We present the instrument design, ground test results, challenges, and highlight some of the flight measurements.

N Ehsan↗

Cybersecurity Vulnerability Mitigation Framework through Empirical Paradigm: Enhanced Prioritized Gap Analysis

Existing cybersecurity vulnerability assessment tools were designed based on the policies and standards defined by organizations such as the U.S. Department of Energy and the National Institute of Standards and Technology (NIST). Frameworks such as the cybersecurity capability maturity model (C2M2) and the NIST Cybersecurity Framework (CSF) are often used by the critical infrastructure owners and operators to determine the cybersecurity maturity of their facility. Although these frameworks are exceptional at performing qualitative cybersecurity analysis and identifying vulnerabilities, they do not provide a means to perform prioritized mitigation of those vulnerabilities in order to achieve a desired cybersecurity maturity. To address that challenge, we developed a framework and software application called the cybersecurity vulnerability mitigation framework through empirical paradigm (CyFEr). This paper presents the detailed architecture of CyFEr’s enhanced prioritized gap analysis (EPGA) methodology and its application to CSF. The efficacy of the presented framework is demonstrated by comparing against existing similar models and testing against the cyber injects from a real-world cyber-attack that targeted industrial control systems (ICS) in critical infrastructures.

Gourisetti, Sri Nikhil G.↗

New Air-Launched Small Missile (ALSM) Flight Testbed for Hypersonic Systems

A new testbed for hypersonic flight research is proposed. Known as the Phoenix air-launched small missile (ALSM) flight testbed, it was conceived to help address the lack of quick-turnaround and cost-effective hypersonic flight research capabilities. The Phoenix ALSM testbed results from utilization of two unique and very capable flight assets: the United States Navy Phoenix AIM-54 long-range, guided air-to-air missile and the NASA Dryden F-15B testbed airplane. The U.S. Navy retirement of the Phoenix AIM-54 missiles from fleet operation has presented an excellent opportunity for converting this valuable flight asset into a new flight testbed. This cost-effective new platform will fill an existing gap in the test and evaluation of current and future hypersonic systems for flight Mach numbers ranging from 3 to 5. Preliminary studies indicate that the Phoenix missile is a highly capable platform. When launched from a high-performance airplane, the guided Phoenix missile can boost research payloads to low hypersonic Mach numbers, enabling flight research in the supersonic-to-hypersonic transitional flight envelope. Experience gained from developing and operating the Phoenix ALSM testbed will be valuable for the development and operation of future higher-performance ALSM flight testbeds as well as responsive microsatellite small-payload air-launched space boosters.

Bui, Trong T.↗

MLtool: Universal Supervised Machine Learning Tool to Model Tabulated Data

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine learning↗