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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Integrating Safety and Mission Assurance into Systems Engineering Modeling Practices

During the early development of products, flight, or experimental hardware, emphasis is often given to the identification of technical requirements, utilizing such tools as use case and activity diagrams. Designers and project teams focus on understanding physical and performance demands and challenges. It is typically only later, during the evaluation of preliminary designs that a first pass, if performed, is made to determine the process, safety, and mission quality assurance requirements. Evaluation early in the life cycle, though, can yield requirements that force a fundamental change in design. This paper discusses an alternate paradigm for using the concepts of use case or activity diagrams to identify safety hazard and mission quality assurance risks and concerns using the same systems engineering modeling tools being used to identify technical requirements. It contains two examples of how this process might be used in the development of a space flight experiment, and the design of a Human Powered Pizza Delivery Vehicle, along with the potential benefits to decrease development time, and provide stronger budget estimates.

Requirements↗
DOE OSTI2023

Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads

Abstract. Floating wind turbines must withstand a unique and challenging set of loads from the wind and ocean environment. To de-risk development, accurate predictions of these loads are necessary. Uncertainty in modeling predictions leads to larger required safety factors, increasing project costs and the levelized cost of energy. Complex aero-hydro-elastic modeling tools use many input parameters to represent the wind, waves, current, aerodynamic loads, hydrodynamic loads, and structural properties. It is helpful to understand which of these parameters ultimately drives a design. In this work, an ultimate and fatigue-proxy load sensitivity analysis was performed with 35 different input parameters, using an elementary effects approach to identify the most influential parameters for a case study involving the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine atop the OC4-DeepCwind semisubmersible during normal operation. The importance of each parameter was evaluated using 14 response quantities of interest across three operational wind speed conditions. The study concludes that turbulent wind velocity standard deviation is the parameter with the strongest sensitivity; this value is important not just for turbine loads, but also for the global system response. The system center of mass in the wind direction is found to have the highest impact on the system rotation and tower loads. The current velocity is found to be the most dominating parameter for the system global motion and consequently the mooring loads. All tested wind turbulence parameters in addition to the standard deviation are also found to be influential. Wave characteristics are influential for some fatigue-proxy loading but do not significantly impact the extreme ultimate loads in these operational load cases. The required number of random seeds for stochastic environmental conditions is considered to ensure that the sensitivities are due to the input parameters and not due to the seed. The required number of analysis points in the parameter space is identified so that the conclusions represent a global sensitivity. The results are specific to the platform, turbine, and choice of parameter ranges, but the demonstrated approach can be applied widely to guide focus in parameter uncertainty.

17 WIND ENERGY↗
NASA NTRS2006

JSC Orbital Debris Website Description

Purpose: The website provides information about the NASA Orbital Debris Program Office at JSC, which is the lead NASA center for orbital debris research. It is recognized world-wide for its leadership in addressing orbital debris issues. The NASA Orbital Debris Program Office has taken the international lead in conducting measurements of the environment and in developing the technical consensus for adopting mitigation measures to protect users of the orbital environment. Work at the center continues with developing an improved understanding of the orbital debris environment and measures that can be taken to control its growth. Major Contents: Orbital Debris research is divided into the following five broad efforts. Each area of research contains specific information as follows: 1) Modeling - NASA scientists continue to develop and upgrade orbital debris models to describe and characterize the current and future debris environment. Evolutionary and engineering models are described in detail. Downloadable items include a document in PDF format and executable software. 2) Measurements - Measurements of near-Earth orbital debris are accomplished by conducting ground-based and space-based observations of the orbital debris environment. The data from these sources provide validation of the environment models and identify the presence of new sources. Radar, optical and surface examinations are described. External links to related topics are provided. 3) Protection - Orbital debris protection involves conducting hypervelocity impact measurements to assess the risk presented by orbital debris to operating spacecraft and developing new materials and new designs to provide better protection from the environment with less weight penalty. The data from this work provides the link between the environment defined by the models and the risk presented by that environment to operating spacecraft and provides recommendations on design and operations procedures to reduce the risk as required. These data also help in the analysis and interpretation of impact features on returned spacecraft surfaces. 4) Mitigation - Controlling the growth of the orbital debris population is a high priority for NASA, the United States, and the major space-faring nations of the world to preserve near-Earth space for future generations. Mitigation measures can take the form of curtailing or preventing the creation of new debris, designing satellites to withstand impacts by small debris, and implementing operational procedures ranging from utilizing orbital regimes with less debris, adopting specific spacecraft attitudes, and even maneuvering to avoid collisions with debris. Downloadable items include several documents in PDF format and executable software.and 5) Reentry - Because of the increasing number of objects in space, NASA has adopted guidelines and assessment procedures to reduce the number of non-operational spacecraft and spent rocket upper stages orbiting the Earth. One method of postmission disposal is to allow reentry of these spacecraft, either from orbital decay (uncontrolled entry) or with a controlled entry. Orbital decay may be achieved by firing engines to lower the perigee altitude so that atmospheric drag will eventually cause the spacecraft to enter. However, the surviving debris impact footprint cannot be guaranteed to avoid inhabited landmasses. Controlled entry normally occurs by using a larger amount of propellant with a larger propulsion system to drive the spacecraft to enter the atmosphere at a steeper flight path angle. It will then enter at a more precise latitude, longitude, and footprint in a nearly uninhabited impact region, generally located in the ocean.

Johnson, Nicholas L.↗
NASA NTRS2008

Integrating Human Factors into Space Vehicle Processing for Risk Management

This presentation will discuss the multiple projects performed in United Space Alliance's Human Engineering Modeling and Performance (HEMAP) Lab, improvements that resulted from analysis, and the future applications of the HEMAP Lab for risk assessment by evaluating human/machine interaction and ergonomic designs.

Woodbury, Sarah↗
DOE OSTI2020

Evaluation of Containment and Geomechanical Risks at Integrated Mid-Content Stacked Carbon Storage Hub Sites

The U.S. Department of Energy is leading the development of CCS through collaborative projects and programs to not only develop and demonstrate the technology but to also quantify the risks and provide tools that site operators can use to develop a site-specific understanding of their risk to enable successful project operations. This report summarizes results and findings from the application of risk-assessment tools to an industrial-scale Geologic Carbon Storage (GCS) project. Specifically, we applied the National Risk Assessment Partnership’s (NRAP) Open Integrated Assessment Model (NRAP-Open-IAM) and State of Stress Assessment Tool (SOSAT) to two candidate sites being considered for storage by the Integrated Midcontinent Stacked Carbon Storage Hub (IMSCS-Hub) project team. These sites, Sleepy Hollow Field in Nebraska and Patterson Field in Kansas, have historical oil and gas production and thus are attractive candidates to store the 50 million metric tons (Mt), which is the CarbonSAFE objective. Because these sites have historical operations, they have a significant number of existing wells that pose a risk for well leakage. Additionally, the storage formations will undergo significant pore pressure perturbation (i.e., increase due to CO 2 injection). Hence, we have selected the two NRAP tools best suited to study the risks associated with well leakage and geomechanical risks. The objective of the study was not only to assess the risk at the site, but to also improve the NRAP tools through application using real site data on an ongoing project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Computational Fluid Dynamics Simulations to Assess Spatial Variability and Optimal Ventilation Scenarios for Biological Laboratory Exposures

A significant amount of uncertainty exists regarding potential human exposure to laboratory biomaterials and organisms in Biosafety Level 2 (BSL-2) research laboratories. Computational fluid dynamics (CFD) modeling is proposed as a way to better understand potential impacts of different combinations of biomaterials, laboratory manipulations, and exposure routes on risks to laboratory workers. Here, in this study, we use CFD models to simulate airborne concentrations of contaminants in an actual BSL-2 laboratory under different configurations. Results show that ventilation configuration, sampling location, and contaminant source location can significantly impact airborne concentrations and exposures. Depending on the source location and airflow patterns, the transient and time-integrated concentrations varied by several orders of magnitude. Contaminant plumes from sources located near a return vent (or exhaust like a fume hood or ventilated biosafety cabinet) are likely to be more contained than sources that are further from the exhaust. Having a direct flow between the source and the exhaust (through-flow condition) may reduce potential exposures to individuals outside the air flow path. Designing a BSL-2 room with ventilation and airflow patterns that maximize through-flow conditions to the return/exhaust vents and minimize dispersion and mixing throughout the room is, therefore, recommended. CFD simulations can also be used to assist in characterizing the impacts of supply and return vent locations, room layout, and source locations on spatial and temporal contaminant concentrations. In addition, proper placement of particle sensors can also be informed by CFD simulations to provide additional characterization and monitoring of potential exposures in BSL-2 facilities.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
NASA NTRS2003

The Chandra X-Ray Observatory Radiation Environmental Model Update

CRMFLX (Chandra Radiation Model of ion FLUX) is a radiation environment risk mitigation tool for use as a decision aid in planning the operation times for Chandra's Advanced CCD Imaging Spectrometer (ACIS) detector. The accurate prediction of the proton flux environment with energies of 100 - 200 keV is needed in order to protect the ACIS detector against proton degradation. Unfortunately, protons of this energy are abundant in the region of space where Chandra must operate. In addition, on-board particle detectors do not measure proton flux levels of the required energy range. CRMFLX is an engineering environment model developed to predict the proton flux in the solar wind, magnetosheath, and magnetosphere phenomenological regions of geospace. This paper describes the upgrades to the ion flux databases for the magnetosphere, magnetosheath, and solar wind regions. These data files were created by using Geotail and Polar spacecraft flux measurements only when the Advanced Composition Explorer (ACE) spacecraft's 0.14 MeV particle flux was below a threshold value. This new database allows for CRMFLX output to be correlated with both the geomagnetic activity level, as represented by the Kp index, as well as with solar proton events. Also, reported in this paper are results of analysis leading to a change in Chandra operations that successfully mitigates the false trigger rate for autonomous radiation events caused by relativistic electron flux contamination of proton channels.

Blackwell, William C.↗
NASA NTRS2011

Genotoxic Effects of Low- and High-LET Radiation on Human Epithelial Cells Grown in 2-D Versus 3-D Culture

Risk estimation for radiation-induced cancer relies heavily on human epidemiology data obtained from terrestrial irradiation incidents from sources such as medical and occupational exposures as well as from the atomic bomb survivors. No such data exists for exposures to the types and doses of high-LET radiation that will be encountered during space travel; therefore, risk assessment for space radiation requires the use of data derived from cell culture and animal models. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. This work compares the genotoxic effects of radiation on normal human epithelial cells grown in standard 2-D monolayer culture compared to 3-D organotypic co-culture conditions. These 3-D organotypic models mimic the morphological features, differentiation markers, and growth characteristics of fully-differentiated normal human tissue and are reproducible using defined components. Cultures were irradiated with 2 Gy low-LET gamma rays or varying doses of high-LET particle radiation and genotoxic damage was measured using a modified cytokinesis block micronucleus assay. Our results revealed a 2-fold increase in residual damage in 2 Gy gamma irradiated cells grown under organotypic culture conditions compared to monolayer culture. Irradiation with high-LET particle radiation gave similar results, while background levels of damage were comparable under both scenarios. These observations may be related to the phenomenon of "multicellular resistance" where cancer cells grown as 3-D spheroids or in vivo exhibit an increased resistance to killing by chemotherapeutic agents compared to the same cells grown in 2-D culture. A variety of factors are likely involved in mediating this process, including increased cell-cell communication, microenvironment influences, and changes in cell cycle kinetics that may promote survival of damaged cells in 3-D culture that would otherwise die or be rendered reproductively inactive in 2-D culture.

Patel, Z. S.↗
DOE OSTI2022

Nonsynonymous amino acid changes in the α-chain of complement component 5 influence longitudinal susceptibility to Plasmodium falciparum infections and severe malarial anemia in kenyan children

Background: Severe malarial anemia (SMA; Hb < 5.0 g/dl) is a leading cause of childhood morbidity and mortality in holoendemic Plasmodium falciparum transmission regions such as western Kenya. Methods: We investigated the relationship between two novel complement component 5 (C5) missense mutations [rs17216529:C>T, p(Val145Ile) and rs17610:C>T, p(Ser1310Asn)] and longitudinal outcomes of malaria in a cohort of Kenyan children (under 60 mos, n = 1,546). Molecular modeling was used to investigate the impact of the amino acid transitions on the C5 protein structure. Results: Prediction of the wild-type and mutant C5 protein structures did not reveal major changes to the overall structure. However, based on the position of the variants, subtle differences could impact on the stability of C5b. The influence of the C5 genotypes/haplotypes on the number of malaria and SMA episodes over 36 months was determined by Poisson regression modeling. Genotypic analyses revealed that inheritance of the homozygous mutant (TT) for rs17216529:C>T enhanced the risk for both malaria (incidence rate ratio, IRR = 1.144, 95%CI: 1.059–1.236, p = 0.001) and SMA (IRR = 1.627, 95%CI: 1.201–2.204, p = 0.002). In the haplotypic model, carriers of TC had increased risk of malaria (IRR = 1.068, 95%CI: 1.017–1.122, p = 0.009), while carriers of both wild-type alleles (CC) were protected against SMA (IRR = 0.679, 95%CI: 0.542–0.850, p = 0.001). Conclusion: Collectively, these findings show that the selected C5 missense mutations influence the longitudinal risk of malaria and SMA in immune-naïve children exposed to holoendemic P. falciparum transmission through a mechanism that remains to be defined.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Future climate doubles the risk of hydraulic failure in a wet tropical forest

Summary Future climate presents conflicting implications for forest biomass. We evaluate how plant hydraulic traits, elevated CO 2 levels, warming, and changes in precipitation affect forest primary productivity, evapotranspiration, and the risk of hydraulic failure. We used a dynamic vegetation model with plant hydrodynamics (FATES‐HYDRO) to simulate the stand‐level responses to future climate changes in a wet tropical forest in Barro Colorado Island, Panama. We calibrated the model by selecting plant trait assemblages that performed well against observations. These assemblages were run with temperature and precipitation changes for two greenhouse gas emission scenarios (2086–2100: SSP2‐45, SSP5‐85) and two CO 2 levels (contemporary, anticipated). The risk of hydraulic failure is projected to increase from a contemporary rate of 5.7% to 10.1–11.3% under future climate scenarios, and, crucially, elevated CO 2 provided only slight amelioration. By contrast, elevated CO 2 mitigated GPP reductions. We attribute a greater variation in hydraulic failure risk to trait assemblages than to either CO 2 or climate. Our results project forests with both faster growth (through productivity increases) and higher mortality rates (through increasing rates of hydraulic failure) in the neo‐tropics accompanied by certain trait plant assemblages becoming nonviable.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Chandra Radiation Environment Modeling

CRMFLX (Chandra Radiation Model of ion FluX) is a radiation environment risk mitigation tool for use as a decision aid in planning the operations times for Chandra's Advanced CCD Imaging Spectrometer (ACIS) detector. The accurate prediction of the proton flux environment with energies of 100 - 200 keV is needed in order to protect the ACIS detector against proton degradation. Unfortunately, protons of this energy are abundant in the region of space Chandra must operate, and on-board particle detectors do not measure proton flux levels of the required energy range. This presentation will describe the plasma environment data analysis and modeling basis of the CRMFLX engineering environment model developed to predict the proton flux in the solar wind, magnetosheath, and magnetosphere phenomenological regions of geospace. The recently released CRMFLX Version 2 implementation includes an algorithm that propagates flux from an observation location to other regions of the magnetosphere based on convective ExB and VB-curvature particle drift motions. This technique has the advantage of more completely filling out the database and makes maximum use of limited data obtained during high Kp periods or in areas of the magnetosphere with poor satellite flux measurement coverage.

Minow, Joseph I.↗
NASA NTRS2016

The NASA Commercial Crew Program (CCP) Mission Assurance Process

In 2010, NASA established the Commercial Crew Program in order to provide human access to the International Space Station and low earth orbit via the commercial (non-governmental) sector. A particular challenge to NASA has been how to determine the commercial providers transportation system complies with Programmatic safety requirements. The process used in this determination is the Safety Technical Review Board which reviews and approves provider submitted Hazard Reports. One significant product of the review is a set of hazard control verifications. In past NASA programs, 100 percent of these safety critical verifications were typically confirmed by NASA. The traditional Safety and Mission Assurance (SMA) model does not support the nature of the Commercial Crew Program. To that end, NASA SMA is implementing a Risk Based Assurance (RBA) process to determine which hazard control verifications require NASA authentication. Additionally, a Shared Assurance Model is also being developed to efficiently use the available resources to execute the verifications. This paper will describe the evolution of the CCP Mission Assurance process from the beginning of the Program to its current incarnation. Topics to be covered include a short history of the CCP; the development of the Programmatic mission assurance requirements; the current safety review process; a description of the RBA process and its products and ending with a description of the Shared Assurance Model.

Commercial Crew Program↗
DOE OSTI2025

First-of-a-Kind Risk-Informed Digital Twin for Operational Decision Making

A digital twin (DT) is a digital model or a collection of models of a physical entity. DTs in the nuclear arena can be used from plant design through decommissioning. Decisions are typically a priori or made offline. Risk-informed decision making is identifying what can go wrong, its frequency, and the consequences of its failure. Ideally risk-informed decision making reflects the current state of the plant and provides a decision in real time. Traditionally, probabilistic risk assessments (PRAs) evaluate the failures of safety systems, the risk of core damage, and the offsite dose as the consequence. However, this DT evaluates the decisions on the control side rather than the protection side. It uses the same risk methods to probabilistically inform the decision-making process but in a different way. Rather than evaluating the risk of core damage, this DT evaluates the likelihood of avoiding a trip set point while maintaining plant safety. Performance-based assessments are identified via its probabilistic evaluation of operational alternatives based on system status. Because the purpose of the control system is to maintain system variables within prescribed operating ranges, upsets or challenges that can exceed a trip set point resulting in a plant transient and a challenge to plant mitigating systems based on actual plant conditions, are evaluated to safely maintain the plant within the operating ranges. The probabilistic portion of the model is autonomously and automatically adjusted, and the metric of interest (i.e. likelihood of avoiding a trip set point) is recalculated. The digital representation of the physical system (i.e. the DT) performs a deterministic performance–based assessment of the probabilistically identified alternatives identified to validate the probabilistic assessment. A decision-making algorithm selects the appropriate option based on the probabilistic and deterministic assessments and transmits a control signal to a component(s) to initiate a corrective action or informs an operator of its decision.

digital twin↗
DOE OSTI2025

Tactical Analysis for Calculating Contextual Risk at Boundaries: Summary of Laboratory Directed Research & Development Effort

The Tactical Analysis for Calculating Contextual Risk at Boundaries (TACCRAB) tool is an innovative digital twin (DT) platform and automated risk algorithm designed to transform operational decision-making in structured screening environments, with an initial focus on Southern Border Land Ports of Entry (POEs). The invention provides integration points for advanced artificial intelligence, predictive modeling, and real-time data analysis to produce a comprehensive risk management tool that enables proactive, data-informed security strategies. The core inventive features of TACCRAB center on its unique risk algorithm, which dynamically calculates contextual risk by synthesizing historical data, near real-time streaming data from the checkpoints themselves, and AI-generated predictions. Unlike traditional risk assessment methods, TACCRAB utilizes a DT to provide comprehensive operational insights, allowing stakeholders to visualize, simulate, and optimize checkpoint configurations with unprecedented speed and contextual awareness. TACCRAB's key innovation lies in its ability to combine multiple complex inputs - including technology detection probabilities, resource availability, screening pathway characteristics, and threat actor behavioral patterns - into a unified risk calculation and update these inputs based on changing operational and environmental conditions. By leveraging a DT that continuously updates and learns from linked data, TACCRAB can suggest adaptive mitigation strategies that minimize risk while maintaining operational efficiency. Particularly novel is the platform's approach to decision support, which goes beyond static risk assessment. The DT provides dynamic metrics such as wait times, resource allocation effectiveness, and potential emerging threat scenarios, enabling users to view sophisticated, relevant what-if simulations and optimize checkpoint operations in near real-time. The system's architecture allows for generalized application across different screening environments, such as secure facilities, ports of entry, and soft targets, making it a versatile tool for security and operational management. The invention distinguishes itself through its comprehensive integration of predictive modeling, AI-driven pattern discovery, and user-friendly interface design. By combining these elements, TACCRAB transforms complex risk data into actionable insights, supporting decision-makers at various organizational levels - from booth agents making split-second screening decisions to checkpoint managers optimizing the day's resource allocation to strategic planners managing long-term investments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS2006

Utilizing a Common Model Architecture for the Simulation of On-Orbit Human Spaceflight Operations

Advances in computing and simulation technology during the 1980 s promoted the development of multiple simulations for on-orbit human spaceflight operations at the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC). By the late 1980 s, it became increasingly clear that redundancy risked leading to inefficiencies in dissemination and incorporation of models across simulations, institutional organizations, and spaceflight programs. Software development tools, such as the Trick Simulation Environment, began to emerge providing a generalized framework for the development, integration, and operation of simulations. Throughout the 1990s, engineering, operations, and training simulations began to migrate to Trick in order to take advantage of a common simulation environment. Due to forecasted reductions in funding to the Shuttle and International Space Station (ISS) programs in the early 2000s, the common framework that arose from this simulation migration was formalized as the Common Model Architecture (CMA). The CMA was established in order to further reduce redundancy, while promoting model sharing and enhancing model integrity. A minimal set of standards for data flows, functional interactions, and model organization based on Trick were defined for those features found to be most important in facilitating model interaction. Model-providing organizations within NASA JSC took ownership of models for their specific areas of expertise, and agreements were reached on common model sharing and usage. This paper describes the evolution of commonality enabled by the Trick Simulation Environment at JSC leading to the CMA, the standards defined by the CMA, a recent CMA simulation example, and potential application of the CMA to NASA s new Exploration program.

Leslie J Quiocho↗
DOE OSTI2024

wa-hls4ml: A GNN Surrogate Model for hls4ml

Recent advancements in use of machine learning techniques on field-programmable gate arrays (FPGAs) have allowed for implementation of embedded neural networks with extremely low latency. This is invaluable for particle detectors at the Large Hadron Collider, where latency and used area must be strictly bounded. The hls4ml framework is a procedure for converting from trained machine learning model software, to a synthesis result that can be used on an FPGA. However, running the pipeline is a time-consuming procedure, and there is a strong risk of failure. In particular, it is possible that the model is unable to be converted into a synthesis result, or that the resource consumption of the model will exceed the resources of the target FPGA. To aid with this development, we introduce wa-hls4ml, a surrogate model which uses a graph neural network to emulate the structure of the source models. The goal is to estimate the chance of success and resource consumption of an arbitrary model when passed through the hls4ml procedure, without the time consumption of actually running the pipeline.

43 PARTICLE ACCELERATORS↗
NASA NTRS2001

Re-Entry Survivability Risk Assessment of the Extreme Ultraviolet Explorer (EUVE)

A reentry analysis of the Extreme Ultraviolet Explorer (EUVE) spacecraft was performed using the Object Reentry Survival Analysis Tool (ORSAT) - Version 5.0. The analysis was done in response to a request by NASA Headquarters and Goddard Space Flight Center (GSFC) after a preliminary assessment using the NASA Johnson Space Center Debris Assessment Software (DAS) - Version 1.0 had shown that the EUVE reentry may produce a debris area greater than the limit set within the NASA Safety Standard 1740.14 guidelines. DAS predicted that an uncontrolled reentry of the EUVE spacecraft would result in a total casualty area of 12.41 sq m, which exceeds the 8 sq m limit set in the NASA standards and implies a potential human casualty risk of approximately 1 in 5300. The ORSAT model enabled a higher fidelity thermal analysis of the EUVE spacecraft, utilizing sophisticated material and thermal properties such as emissivity, heat of oxidation, thermal conductivity, and material thickness inputs, which provided a foundation for a more in depth analysis of the reentering objects. Due to the conservative nature of the DAS study, it was reasonable to run ORSAT for only the ten objects shown to survive in the original DAS analysis. The result of the ORSAT study was a reduced casualty area of only 5.95 sq m, well within NASA safety limits. With the risk to human life now acceptably low, NASA can avoid having to take mitigation measures and allow EUVE to reenter the Earth's atmosphere uncontrolled.

O'Hara, Robin E.↗
DOE OSTI2023

Dynamic Asset Allocation with Expected Shortfall via Quantum Annealing

Recent advances in quantum hardware offer new approaches to solve various optimization problems that can be computationally expensive when classical algorithms are employed. We propose a hybrid quantum-classical algorithm to solve a dynamic asset allocation problem where a target return and a target risk metric (expected shortfall) are specified. We propose an iterative algorithm that treats the target return as a constraint in a Markowitz portfolio optimization model, and dynamically adjusts the target return to satisfy the targeted expected shortfall. The Markowitz optimization is formulated as a Quadratic Unconstrained Binary Optimization (QUBO) problem. The use of the expected shortfall risk metric enables the modeling of extreme market events. We compare the results from D-Wave’s 2000Q and Advantage quantum annealers using real-world financial data. Both quantum annealers are able to generate portfolios with more than 80% of the return of the classical optimal solutions, while satisfying the expected shortfall. We observe that experiments on assets with higher correlations tend to perform better, which may help to design practical quantum applications in the near term.

97 MATHEMATICS AND COMPUTING↗