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NASA NTRS2014

A Historical Analysis of Crane Mishaps at Kennedy Space Center

Cranes and hoists are widely used in many areas. Crane accidents and handling mishaps are responsible for injuries, costly equipment damage, and program delays. Most crane accidents are caused by preventable factors. Understanding these factors is critical when designing cranes and preparing lift plans. Analysis of previous accidents provides insight into current recommendations for crane safety. Cranes and hoists are used throughout Kennedy Space Center to lift everything from machine components to critical flight hardware. Unless they are trained crane operators, most NASA employees and contractors do not need to undergo specialized crane training and may not understand the safety issues surrounding the use of cranes and hoists. A single accident with a crane or hoist can injure or kill people, cause severe equipment damage, and delay or terminate a program. Handling mishaps can also have a significant impact on the program. Simple mistakes like bouncing or jarring a load, or moving the crane down when it should go up, can damage fragile flight hardware and cause major delays in processing. Hazardous commodities (high pressure gas, hypergolic propellants, and solid rocket motors) can cause life safety concerns for the workers performing the lifting operations. Most crane accidents are preventable with the correct training and understanding of potential hazards. Designing the crane with human factors taken into account can prevent many accidents. Engineers are also responsible for preparing lift plans where understanding the safety issues can prevent or mitigate potential accidents. Cranes are widely used across many areas of KSC. Failure of these cranes often leads to injury, high damage costs, and significant delays in program objectives. Following a basic set of principles and procedures during design, fabrication, testing, regular use, and maintenance can significantly minimize many of these failures. As the accident analysis shows, load drops are often caused or influenced by human factors. Therefore, proper training and understanding of crane safety throughout the workforce is critical. It is important that the engineers designing the cranes, lift planners preparing the lift plans, operators performing the lifts, and training officers conducting the operator training all understand the problems that can happen with cranes and how to ensure the safety of the workforce and equipment being lifted.

Materials Handling↗

DOE OSTI2025

Utility-Scale Operational Consequences for Solar Grid Services

This report delves into the critical aspects of grid services provided by solar inverter-based resources (IBRs), with an emphasis on the evolving landscape of microgrids, virtual power plants (VPPs), aggregators, and distributed energy resource management systems (DERMS). As the energy sector undergoes a transformative shift towards more decentralized and resilient grid architectures, understanding the multifaceted risks associated with these technologies becomes paramount. The report categorizes these risks into organizational, technical, and procedural domains, providing a thorough risk assessment framework that stakeholders can utilize to anticipate and mitigate potential issues. In addressing the increasing complexity of grid interconnections, the report highlights the importance of Cyber-Informed Engineering (CIE). By embedding engineering controls and cybersecurity measures into the early stages of system design, this approach aims to fortify grid infrastructure against emerging cyber threats. The analysis includes an exploration of best practices and strategies for integrating CIE principles to enhance grid security and resilience. To provide practical insights, the report conducts a detailed consequence analysis of various grid services and cyber mitigations that can be applied through the interconnection process. This analysis evaluates the potential impacts of different failure modes and vulnerabilities, offering a clear understanding of the consequences that could arise from disruptions within the energy grid. The findings are further enriched by a series of case studies that illustrate real-world scenarios and lessons learned from past incidents. Through this comprehensive examination of grid services and their criticality, the report aims to prepare industry professionals with the knowledge and tools necessary to navigate the complexities of modern energy systems. By providing a comprehensive approach that includes risk assessment, cybersecurity, and consequence analysis, solar stakeholders can more effectively guarantee the reliability, efficiency, and security of the energy grid.

14 SOLAR ENERGY↗

DOE OSTI2020

Well-to-wheels greenhouse gas and air pollutant emissions from battery electric vehicles in China

Electric vehicles (EVs) play a crucial role in addressing climate change and urban air quality concerns. China has emerged as the global largest EV market with 1.2 million EVs sold in 2018. This study established a novel life cycle energy use and emission inventory collecting up-to-date data including the electricity generation mix, emission controls in the power and industrial sectors, and the energy use in the fuel transport to estimate the well-to-wheels (WTW) greenhouse gas (GHG), and air pollutant emissions for battery electric vehicles (BEVs) and gasoline passenger vehicles in China. The results show that an average BEV has 35% lower WTW GHG emissions than an average gasoline car. BEVs reduce volatile organic compounds (VOCs) and nitrogen oxides (NOX) emissions by 98% and 34%, respectively, but have comparable or slightly higher primary fine particulate matter (PM2.5) and sulfur dioxide (SO2) emissions. Compact and small-size vehicles generally have lower GHG and air pollutant emissions than mid- and large-size vehicles. Class A vehicles contribute the most in the absolute amount of GHG and air pollutant emissions and therefore have the biggest potential for emission reduction. Our results suggest that global policymakers should continue to promote the transition to clean power sources, emission control, and fuel economy regulations, which are critical to enhancing emission mitigation benefits of BEVs. We also suggest EV development strategies should be formulated targeting vehicle class with the biggest emission mitigation potentials.

Air pollutant emissions↗

NASA NTRS2013

How Cities Breathe: Ground-Referenced, Airborne Hyperspectral Imaging Precursor Measurements To Space-Based Monitoring

Methane's (CH4) large global warming potential (Shindell et al., 2012) and likely increasing future emissions due to global warming feedbacks emphasize its importance to anthropogenic greenhouse warming (IPCC, 2007). Furthermore, CH4 regulation has far greater near-term climate change mitigation potential versus carbon dioxide CO2, the other major anthropogenic Greenhouse Gas (GHG) (Shindell et al., 2009). Uncertainties in CH4 budgets arise from the poor state of knowledge of CH4 sources - in part from a lack of sufficiently accurate assessments of the temporal and spatial emissions and controlling factors of highly variable anthropogenic and natural CH4 surface fluxes (IPCC, 2007) and the lack of global-scale (satellite) data at sufficiently high spatial resolution to resolve sources. Many important methane (and other trace gases) sources arise from urban and mega-urban landscapes where anthropogenic activities are centered - most of humanity lives in urban areas. Studying these complex landscape tapestries is challenged by a wide and varied range of activities at small spatial scale, and difficulty in obtaining up-to-date landuse data in the developed world - a key desire of policy makers towards development of effective regulations. In the developing world, challenges are multiplied with additional political access challenges. As high spatial resolution satellite and airborne data has become available, activity mapping applications have blossomed - i.e., Google maps; however, tap a minute fraction of remote sensing capabilities due to limited (three band) spectral information. Next generation approaches that incorporate high spatial resolution hyperspectral and ultraspectral data will allow detangling of the highly heterogeneous usage megacity patterns by providing diagnostic identification of chemical composition from solids (refs) to gases (refs). To properly enable these next generation technologies for megacity include atmospheric radiative transfer modeling the complex and often aerosol laden, humid, urban microclimates, atmospheric transport and profile monitoring, spatial resolution, temporal cycles (diurnal and seasonal which involve interactions with the surrounding environment diurnal and seasonal cycles) and representative measurement approaches given traffic realities. Promising approaches incorporate contemporaneous airborne remote sensing and in situ measurements, nocturnal surface surveys, with ground station measurement

Leifer, Ira↗

NASA NTRS2024

Quantifying Food Security and Mitigation Risks Consequential to Climate Change Impacts on Crop Yields

Climate change is expected to impact crop yields globally, with some regions benefiting from favorable conditions and CO2 fertilization, while others face adverse effects from altered precipitation and higher temperatures. Changes in crop yields can destabilize the global food system and pose challenges to food security. Moreover, crop production is crucial, as biofuels are becoming increasingly important contributors to climate change mitigation measures aimed at limiting global warming. This study uses the Integrated Model to Assess the Global Environment integrated assessment model framework to analyze different indicators related to food security and climate change mitigation under varying climate change impacts on crop yields. Twelve spatially explicit crop productivity projections were taken from the full archive of the Global Gridded Crop Model Intercomparison of 120 climate-crop model combinations, forced by CMIP6-based climate scenarios. The selection includes two average-performing climate-crop model combinations, two pessimistic combinations that perform one standard deviation below the mean, and two optimistic model combinations that perform one standard deviation above the mean. To single out the effect of climate change on productivity changes, we drew samples from two representative concentration pathways (RCP2.6 and RCP8.5). These productivity projections were applied within an otherwise uniform scenario (SSP2) and analyzed for their effect on total calorie demand, crop prices, and number of people at risk of undernourishment to quantify food security. Risks to climate change mitigation targets were explored by modeling the total bioenergy supply, emissions, and global mean temperature. The results revealed significant differences in the risk of food security and mitigation potential between different regions and climate change scenarios. Across scenarios, the crop area extent can vary up to 2 million km2 due to changing crop yields. The projected change in global hunger ranges from 60 to 160 million undernourished people, indicating uncertainty between climate and crop model combinations. Low-income regions are especially impacted because of their high sensitivity to changes in food prices. Global climate change mitigation ambitions can also deviate by the latter part of the 21st century, as changes in yields will impact biofuel production as well as agriculture, forestry and other land use emissions. The quantitative insights generated by this study highlight the need for global policy efforts to make the agricultural system more adaptive to climate change to handle potential negative impacts.

crop yields↗

DOE OSTI2025

A Near-Real-Time Model for Predicting Electricity Disruptions in Texas During Winter Storms

There has been an increase in extreme weather events, posing a threat to power grid systems, potentially influenced by factors such as population growth, changes in ecosystems, land cover, and land use in the service area, as well as the growth of certain vegetation types. This research seeks to develop a predictive model to mitigate potential damages caused by future winter storms. This research utilizes the Light Gradient Boosting Machine (LightGBM), incorporating the number of power outages experienced at the county level, geographic details, weather information, and lagged outage and lagged weather data. The developed models were broadly divided into two groups, with six models in each group - one group without optimization and another with optimization, totaling 12 trained models. For model optimization, Bayesian optimization was employed using Root Mean Squared Error (RMSE) as the objective function. In results, when comparing Group 2 (the optimized group) with Group 1 (the non-optimized group), it was found that optimization did not always lead to a reduction in RMSE and Mean Absolute Error (MAE). However, in terms of Mean Directional Accuracy (MDA), while all results in Group 1 were below the baseline accuracy of 0.33, all results in Group 2 exceeded 0.33, with some cases showing an increase of more than three times the baseline. The results indicated that, in the optimized model group, Population and Pressure were the most influential factors when using current weather data and geographical information. When using lagged data, lagged recorded outages and lagged Pressure emerged as the most significant factors. Among the 12 developed models, the L-1-2-O model showed the lowest RMSE and MAE, as well as the highest accuracy, with values of 390.62 households and 168.13 households, respectively. To normalize the RMSE and MAE values, each metric was divided by the average number of households among the counties in Texas. For the L-1-2-O model, the scaled RMSE was 0.88% and the scaled MAE was 0.38%. In terms of MDA, which indicates the accuracy of the prediction direction, the L-1-O model achieved the highest score of 0.41. Although this study focused on Texas, which suffered the greatest impact from the winter storms in 2021, with additional validation, the methodology used in this research could be applied to other regions.

Lee, Jangjae [Texas A & M Univ., College Station, ↗

NASA NTRSDate not supplied

Assessment of the State of Communication Delay Research in Preparation for Missions Beyond Low Earth Orbit

NASA’s mission-operations paradigm, established during Project Mercury and minimally evolving through the Apollo Program, Space Shuttle Program, and ISS missions, has primarily depended on real-time support from a ground team of experts. This ground team has served as the safety net for crewed spaceflight missions over the past 60 years, managing the combined state of the mission, vehicle, and crew. However, this operational paradigm, which has seen little change in its Human-Systems Integration Architecture (HSIA), will face challenges during long-duration exploration missions beyond low Earth orbit. Lunar missions may experience one-way communication latencies ranging from 3 to 14 seconds, while Mars missions will encounter up to a 44-minute round-trip latency at a maximum distance from Earth. Communication delays negatively impact the behavioral health and performance of individuals and crews operating across the multi-team space-to-ground system. Previous research indicates that increased isolation and the challenges posed by delayed communication lead to heightened stress, frustration, adverse behavioral symptoms, and reduced individual performance. NASA has investigated the nature and effectiveness of managing this shift in complex operations since early 2000, but additional research is necessary to assess the issues associated with communication latencies and identify effective countermeasures. This work aimed to examine the evidence from 20 years of research on comm delays. We systematically reviewed the past 20 years of communication delay literature, focusing on how this research aligns with relevant, high-priority needs in the HSIA, Team, and BMed Risks. This type of panoramic review has not been done since 2013; a current, aggregated picture of what has been studied and how is needed to inform additional studies and mitigation development. Additional perspectives were gained from interviews with the research participants, operations experts, and communication delay researchers. Results from this effort will help characterize the risk posed by communication latency for upcoming Artemis missions and point toward potential mitigations. The final results will be presented. For the literature review, we formed a search term seed set drawing from languages used in two papers representative of the previous state of knowledge and supplemented it with additional search terms. We conducted literature searches on Google Scholar, PubMed, and Web of Science and searched NASA project archives for output from NASA-sponsored research. This search yielded 150 papers, of which 48 were relevant. SME interviews provided perspective on key communication delay issues and concerns and what is being worked on to mitigate those issues. Preliminary results of the literature review have been presented. Final results to be presented include the results of the literature review and findings from the interviews.

literature review↗

DOE OSTI2022

Catalyst Deactivation and Its Mitigation during Catalytic Conversions of Biomass

Biofuel or biochemical production from biomass, especially lignocellulosic biomass, is the most promising option to replace fossil-based products to achieve sustainability. However, biomass is currently under-utilized because biomass conversion technologies have faced significant challenges to compete with incumbent petroleum technologies. Advancement in catalysis plays a central role in increasing the readiness of biomass conversion technologies. In this respect, improving catalyst stability is one of the well-known grand challenges for biomass conversion catalysis, which impedes the scaling up and commercialization of many biomass conversion techniques. In comparison to conventional processing of fossil fuels (petroleum, coal, and natural gas), biomass conversion is largely challenged by three unique properties of biomass-derived feedstocks—high water and oxygen content, high degree and reactivity of oxygen functionalization, and high contamination by minerals and heteroatoms—which all cause greater catalyst deactivation in different ways. Therefore, research on catalyst deactivation mitigation and catalyst regeneration is extremely important for the development of biomass conversion technologies. This review aims to highlight studies on catalyst deactivation and mitigation for catalytic processes in biomass conversion, with emphasis on the deactivation caused by the three unique characteristics of biomass-derived feedstocks. Further, this work will provide information on correlating the characteristics of biomass-derived streams, their potential impact on catalyst lifetime, and a potential mitigation approach, which could guide a more rational design of a robust catalyst and processes for biomass conversion.

09 BIOMASS FUELS↗

DOE OSTI2025

A multi model ensemble reveals net climate benefits from regenerative practices in US Midwest croplands

Process-based cropping systems models (CSMs) are key components of measurement, monitoring, reporting, and verification frameworks of carbon markets, but model-specific differences limit their applicability across diverse pedo-climatic conditions and agronomic practices. Multi-model ensemble (MME) provides an opportunity to better estimate changes in soil organic carbon (SOC) and nitrous oxide (N 2 O) emissions from agronomic practices at scale. We used an MME across 46 million hectares of US Midwest cropland at a resolution of 4-km 2 to assess the aggregate ability of different regenerative practices to sequester SOC and N 2 O emissions compared to their counterfactual dynamic baselines. MME was validated against long-term trials and compared to its constituent CSMs, showing greater accuracy and lower uncertainty. The results show that adopting no-till combined with cover crops increased SOC stocks by 0.36 ± 0.12 Mg ha -1 yr -1 , corresponding to a net regional SOC gain of 16.4 Tg C yr -1 compared to business-as-usual baselines. These benefits are halved when each management is practiced individually, and the SOC gains are only fully realized with low initial carbon stock. By including N 2 O emissions, we can assess the overall climate mitigation potential, specifically, the extent to which carbon sequestration can offset direct N 2 O emissions. The magnitude of this potential varies depending on management practices and geographic location with net climate benefits on average ranging from 0 to 3 Mg CO 2 -eq ha -1 yr -1 . High-resolution MME results allow for robust estimates of climate mitigation, reducing barriers to carbon market participation and supporting regenerative agriculture initiatives at scale.

carbon credits↗

NASA NTRS2021

ICESat-2 Constraint Analysis and Monitoring System (CAMS)

The Ice, Cloud and land Elevation Satellite-2 was launched on 15 September 2018 with mission goals of collecting surface elevation data that can precisely measure ice sheet topography, cloud and aerosol heights, land topography, as well as vegetation height for ecosystems studies. The Constraint Analysis and Monitoring System (CAMS) was implemented as an ICESat-2 ground system element to perform Mission Planning and Spacecraft Safety Monitoring. Mission Planning requires CAMS to serve as an interface between the Project Science Office, the Instrument Support Facility and the Mission Operation Control Center. By ingesting inputs received from all three groups, the CAMS builds an optimized and deconflicted timeline of science and instrument activities. Based upon the timeline of activities, the CAMS utilizes a sophisticated set of algorithms to model and predict the location and pointing of the spacecraft instrument relative to the Earth and Sun. From the predicted position and pointing, the CAMS provides precise monitoring of instrument health, and performs space asset laser conjunction detection. Furthermore, the CAMS determines alternative plans to prevent detected health constraint violations or mitigate potential laser conjunctions. This paper provides an overview of the CAMS and presents the operational performance of planning science and instrument activities, the monitoring of instrument constraints for health and safety, and the space asset laser conjunction screening and mitigation process.

ICESat-2↗

NASA NTRS2005

Bridging the Divide between Safety and Risk Management for your Project or Program

This presentation will bridge the divide between these separate but overlapping disciplines and help explain how to use Risk Management as an effective management decision support tool that includes safety. Risk Management is an over arching communication tool used by management to prioritize and effectively mitigate potential problems before they concur. Risk Management encompasses every kind of potential problem that can occur on a program or project. Some of these are safety issues such as hazards that have a specific likelihood and consequence that need to be controlled and included to show an integrated picture of accepted) mitigated, and residual risk. Integrating safety and other assurance disciplines is paramount to accurately representing a program s or projects risk posture. Risk is made up of several components such as technical) cost, schedule, or supportability. Safety should also be a consideration for every risk. The safety component can also have an impact on the technical, cost, and schedule aspect of a given risk. The current formats used for communication of safety and risk issues are not consistent or integrated. The presentation will explore the history of these disciplines, current work to integrate them, and suggestions for integration for the future.

Lutomski, Mike↗

NASA NTRS2023

Heat Stress to Jeopardize Crop Production in the US Corn Belt Based on Downscaled CMIP5 Projections

CONTEXT Global food security faces increasing challenges from the changing climate. Changes of agricultural output from some of the most productive regions such as the US Corn Belt can largely affect the world's food market. Developing predictive understanding of the agricultural risk of climate change and potential mitigation strategies is critical for the global food security. OBJECTIVE The objective of this study is to assess the responses of maize and soybean yield to projected climate changes in the Corn Belt, identify the shifting environment stressors on crop yield, and tackle potential climate adaptation strategies. METHODS We drive a process-based model, the Decision Support System for Agrotechnology Transfer, with high-resolution statistically downscaled and bias-corrected historical and future climates from ten CMIP5 models in the MACA-2 database. RESULTS AND CONCLUSIONS The multi-model ensemble mean suggests a 12% decrease of maize yield by mid-century and 40% by late century, with a high degree of model consensus in the direction of changes; for individual models, the projected decrease of maize yield by late century ranges from <5% to over 80%, with the worst crop outcome corresponding to the most sensitive climate models. Soybean yield is projected to increase by midcentury with a high degree of model consensus, but such consensus is lost by late century as some projections shift to significant decreases. Crop yield in the Corn Belt is currently limited by water stress, but is projected to be increasingly limited by heat stress as well after the midcentury. The mounting heat stress will drive the most productive zone for maize to shift from central to northern part of the Corn Belt, but the projected increase in the northern states cannot fully compensate for the decrease in the south, causing the total production to decrease if agricultural practice stays the same. Earlier planting can alleviate only a small fraction of the heat-induced crop loss in a warmer climate. Climate change will (at least partially) offset the yield boost caused by agricultural technology and intensification. SIGNIFICANCE This study advances our predictive understanding of crop yield responses to climate change, and suggests that a multitude of strategies will be needed to address the climate change challenges for the U.S. agriculture.

Crop yield↗

NASA NTRSDate not supplied

Mapping Mitigation Risk Consequence for Crew Needing Assistance or Rescue on the Lunar Surface

Extravehicular activity (EVA) on the lunar surface presents unique risks to crew with possibility for injury. Without appropriate assistance or rescue capability, inability to nominally ambulate and return to a lander, especially during early Artemis missions, could have catastrophic consequences. Mapping likelihood and consequence safety risk associated with identified injury scenarios establishes a baseline from which to assess potential mitigation solutions to ensure crew health and safety.

lunar surface↗

NASA NTRSDate not supplied

Monitoring of Ionic Silver Biocide with Capacitively-Coupled Contactless Conductivity Detection (C4D)

Monitoring of biocide dosing in spacecraft potable water systems is desirable to ensure dosing system operation and resultant microbial control. Electrolytic conductivity is linearly related to the concentration ionic silver (Ag+, the baseline biocide for future NASA missions) chemically dosed into highly purified water, and could serve as a proxy measurement. Traditional conductivity cells rely on immersed metal or graphite electrodes, which may potentially be subject to significant current-induced or auto-galvanic deposition of Ag+. Furthermore, oxide fouling may potentially induce measurement errors. Capacitively-coupled contactless conductivity detection (C4D) is a promising alternative. C4D uses electrodes placed outside an inert, non-conductive flow path, potentially mitigating such problems. We identified and purchased a commercial C4D system with claimed performance (conductivity range: 20 nS/cm to 4 µS/cm) appropriate for this application. We characterized the instrument’s performance with conductivity standards and Ag+ solutions. We began investigations considering practical and long-term detector operation, including potential current-induced deposition of conductive deposits at the tubing wall. In addition, we designed a side-stream flow system to provide liquid flow through the narrow tubing (1/16” outer diameter) required by the detector and characterized the performance of the combined C4D detector/flow system. Finally, we completed theoretical modeling of expected conductivity change with multiple dosing techniques and water chemistries.

Lance Dean Delzeit↗

NASA NTRS2013

An Approach to Detect and Mitigate Ice Particle Accretion in Aircraft Engine Compression Systems

The accretion of ice in the compression system of commercial gas turbine engines operating in high ice water content conditions is a safety issue being studied by the aviation sector. While most of the research focuses on the underlying physics of ice accretion and the meteorological conditions in which accretion can occur, a systems-level perspective on the topic lends itself to potential near-term operational improvements. This work focuses on developing an accurate and reliable algorithm for detecting the accretion of ice in the low pressure compressor of a generic 40,000 lbf thrust class engine. The algorithm uses only the two shaft speed sensors and works regardless of engine age, operating condition, and power level. In a 10,000-case Monte Carlo simulation, the detection approach was found to have excellent capability at determining ice accretion from sensor noise with detection occurring when ice blocks an average of 6.8 percent of the low pressure compressor area. Finally, an initial study highlights a potential mitigation strategy that uses the existing engine actuators to raise the temperature in the low pressure compressor in an effort to reduce the rate at which ice accretes.

May, Ryan D.↗

NASA NTRS2013

An Approach to Detect and Mitigate Ice Particle Accretion in Aircraft Engine Compression Systems

The accretion of ice in the compression system of commercial gas turbine engines operating in high ice water content conditions is a safety issue being studied by the aviation sector. While most of the research focuses on the underlying physics of ice accretion and the meteorological conditions in which accretion can occur, a systems-level perspective on the topic lends itself to potential near-term operational improvements. This work focuses on developing an accurate and reliable algorithm for detecting the accretion of ice in the low pressure compressor of a generic 40,000 lbf thrust class engine. The algorithm uses only the two shaft speed sensors and works regardless of engine age, operating condition, and power level. In a 10,000-case Monte Carlo simulation, the detection approach was found to have excellent capability at determining ice accretion from sensor noise with detection occurring when ice blocks an average of 6.8% of the low pressure compressor area. Finally, an initial study highlights a potential mitigation strategy that uses the existing engine actuators to raise the temperature in the low pressure compressor in an effort to reduce the rate at which ice accretes.

May, Ryan D.↗

DOE OSTI2023

Project: Corbomite - Product: ConsoleWorks REACT

TDi Technologies presents ConsoleWorks REACT, an advanced platform designed to tackle the complexities of cyber and operational risk assessment. This comprehensive solution goes beyond asset-focused approaches by considering the impact of both assets and people have on the security and operation of critical infrastructure, specifically targeting preventing gird mis-operation by evaluating real-time human interaction or commands with critical assets. The hypothesis suggests that by integrating the assessment of user commands into the overall risk assessment process, organizations can make more informed decisions, prioritize resources effectively, and respond promptly to potential threats. This hypothesis forms the basis for the development of a proactive and holistic risk management approach that is more comprehensive and context aware than traditional models which only look at assets, patch levels, configuration and threat intel by collecting that information off the network vs directly from the asset, human, and human interaction all in real-time. ConsoleWorks' unique man-in-the-middle architecture is a key feature that sets it apart in the cybersecurity landscape. This architecture enables the real-time observation, enforcement, and commands or interaction risk transparency of user interaction with critical infrastructure to be risk mitigated and audited as they are aggregated with device and human risk factors for a more comprehensive risk threat score across a device or group of devices. This architecture allows ConsoleWorks to act as a secure intermediary between users and critical assets, monitoring all interactions and ensuring that only authorized commands are sent to the asset to be executed. This not only enhances security but also provides a comprehensive audit trail of all user activities, contributing to compliance efforts and facilitating incident investigation and risk management. By integrating this unique architecture with our comprehensive risk assessment methodology, ConsoleWorks REACT provides a powerful solution for managing cyber and operational risks, enabling organizations to maintain a robust security posture and effectively mitigate potential threats. To that end, the primary objective of this project was to research and develop a robust solution that enables the energy industry to mitigate the risks associated with human actions that can compromise the security or operations of assets critical to energy delivery, generation, transmission and operation. ConsoleWorks REACT plays a pivotal role in achieving this goal by leveraging its unique capabilities to monitor and track all user activity. Through its Zero Trust approach, which emphasizes continuous verification, the platform ensures secure access to assets and serves as the centralized human response and notification platform for addressing cyber and operational issues.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Adversarial methods to reduce simulation bias in neutrino interaction event filtering at liquid argon time projection chambers

For current and future neutrino oscillation experiments using large liquid argon time projection chambers (LAr-TPCs), a key challenge is identifying neutrino interactions from the pervading cosmic-ray background. Rejection of such background is often possible using traditional cut-based selections, but this typically requires the prior use of computationally expensive reconstruction algorithms. This work demonstrates an alternative approach of using a 3D submanifold sparse convolutional network trained on low-level information from the scintillation light signal of interactions inside LAr-TPCs. This technique is applied to example simulations from ICARUS, the far detector of the short baseline neutrino program at Fermilab. The results of the network, show that cosmic background is reduced by up to 76.3% whilst neutrino interaction selection efficiency remains over 98.9%. We further present a way to mitigate potential biases from imperfect input simulations by applying domain adversarial neural networks (DANNs), for which modified simulated samples are introduced to imitate real data and a small portion of them are used for adversarial training. A series of mock-data studies are performed and demonstrate the effectiveness of using DANNs to mitigate biases, showing neutrino interaction selection efficiency performances significantly better than that achieved without the adversarial training.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗