Search NASA⌕ Search

SEARCH · Search NASA

Results for “MITIGATION STRATEGIES”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

NASA Lunar Surface Innovation Initiative: Ensuring a Cohesive, Executable Strategy for Technology Development

Establishing a sustainable human presence on the Moon allows NASA to develop and test new approaches, technologies, and systems that will enable us to function in other, more challenging environments. The Lunar Surface Innovation Initiative (LSII) was established in 2019 and has evolved into a key agency asset to spur technology development and provide risk reduction for lunar surface system development and flight demonstrations. LSII coordinates activities implemented through a combination of in-house activities, competitive programs, and public-private partnerships to create transformative technologies needed for lunar surface exploration. This paper will outline the LSII model used to develop a technology pipeline that will retire the primary technology hurdles in six capability areas. In-situ resource utilization technologies for collecting, processing, storing, and using material found or manufactured on the Moon. Surface power technologies that provide the capability for sustainable, continuous power throughout the day and night for lunar missions. Dust mitigation strategies that diminish lunar dust hazards on lunar surface systems such as cameras, solar panels, space suits, habitats, and instrumentation. Extreme environments technologies that enable systems to operate throughout the full range of lunar surface conditions, including lunar noon (up to 150 at the equator), night (down to - 180 at the equator), multiple day/night cycles, and in permanently shadowed regions (down to -250). Extreme access technologies that enable humans or robotic systems to access, navigate, and explore previously inaccessible lunar surface or subsurface areas. Excavation and construction technologies that will allow affordable, autonomous manufacturing or construction. We outline key results, including milestones and achievements related to the capability areas and outcomes from partnerships with the commercial sector. A key tenet of the LSII is the Lunar Surface Innovation Consortium (LSIC), a collaboration across industry, academia, and government to successfully develop the transformative capabilities for lunar surface exploration. LSIC provides a forum for NASA to communicate technological requirements, needs, and opportunities and for the community to share existing capabilities and identify critical gaps with NASA. By working side by side with commercial enterprises and our international partners, NASA is able to combine the knowledge and expertise needed to explore the lunar surface and make technical advances that will feed technological and economic growth. Since its inception, LSII has engaged over 600 organizations across the United States and 46 countries to shape the technologies and systems needed to explore the lunar surface and stimulate a lunar surface economy.

lunar, lunar surface, technology development, ISRU↗
DOE OSTI2023

Trade and Climate Mitigation Interactions Create Agro–Economic Opportunities With Social and Environmental Trade–Offs in Latin America and the Caribbean

The Latin America and the Caribbean (LAC) region plays key roles in both meeting global agricultural demands and maintaining carbon sinks due to its abundant land and water resources. In this study we use the Global Change Analysis Model (GCAM) to evaluate the opportunities and challenges posed by two global-scale drivers: agricultural market integration (i.e., reduction of trade barriers) and land-based climate mitigation policy. We evaluate their potential individual and combined impacts on agricultural production and trade revenues across LAC’s economies through mid-century, as well as the resulting impacts on agricultural consumers and integrated land-water-climate systems across the region’s diverse sub-regions. Increased global market integration results in increased agricultural production and trade revenues for many LAC economies driven by their evolving comparative advantages. Climate mitigation measures on CO 2 and non-CO 2 greenhouse gases increase revenues due to increased agricultural prices from land competition and emissions abatement. The combined outcomes from both drivers are complex and sometimes non-linear, highlighting the importance of understanding the interactions between multiple drivers. Our results show that increased agricultural production and trade opportunities pose significant trade-offs that require careful multi-sectoral planning, such as emissions reduction challenges, potential loss of livestock production when pursuing land-based climate mitigation strategies, increased consumer expenditures, and changes in land-use or water withdrawals, resulting in deforestation or water scarcity pressures. There is considerable heterogeneity in economic and environmental outcomes across LAC sub-regions and agricultural commodities, illustrating the value of considering outcomes at finer scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Cost effectiveness of preemptive school closures to mitigate pandemic influenza outbreaks of differing severity in the United States

Background: Nonpharmaceutical interventions (NPIs) may be considered as part of national pandemic preparedness as a first line defense against influenza pandemics. Preemptive school closures (PSCs) are an NPI reserved for severe pandemics and are highly effective in slowing influenza spread but have unintended consequences. Methods: We used results of simulated PSC impacts for a 1957-like pandemic (i.e., an influenza pandemic with a high case fatality rate) to estimate population health impacts and quantify PSC costs at the national level using three geographical scales, four closure durations, and three dismissal decision criteria (i.e., the number of cases detected to trigger closures). At the Chicago regional level, we also used results from simulated 1957-like, 1968-like, and 2009-like pandemics. Our net estimated economic impacts resulted from educational productivity costs plus loss of income associated with providing childcare during closures after netting out productivity gains from averted influenza illness based on the number of cases and deaths for each mitigation strategy. Results: For the 1957-like, national-level model, estimated net PSC costs and averted cases ranged from $\$7.5$ billion (2016 USD) averting 14.5 million cases for two-week, community-level closures to $\$97$ billion averting 47 million cases for 12-week, county-level closures. We found that 2-week school-by-school PSCs had the lowest cost per discounted life-year gained compared to county-wide or school district–wide closures for both the national and Chicago regional-level analyses of all pandemics. The feasibility of spatiotemporally precise triggering is questionable for most locales. Theoretically, this would be an attractive early option to allow more time to assess transmissibility and severity of a novel influenza virus. However, we also found that county-wide PSCs of longer durations (8 to 12 weeks) could avert the most cases (31–47 million) and deaths (105,000–156,000); however, the net cost would be considerably greater ($\$88$-$\$103$ billion net of averted illness costs) for the national-level, 1957-like analysis. Conclusions: We found that the net costs per death averted ($\$180,000$-$\$4.2$ million) for the national-level, 1957-like scenarios were generally less than the range of values recommended for regulatory impact analyses ($\$4.6$ to 15.0 million). This suggests that the economic benefits of national-level PSC strategies could exceed the costs of these interventions during future pandemics with highly transmissible strains with high case fatality rates. In contrast, the PSC outcomes for regional models of the 1968-like and 2009-like pandemics were less likely to be cost effective; more targeted and shorter duration closures would be recommended for these pandemics.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2012

Human Health Countermeasures (HHC) Element Management Plan: Human Research Program

NASA s Human Research Program (HRP) is an applied research and technology program within the Human Exploration and Operations Mission Directorate (HEOMD) that addresses human health and performance risk mitigation strategies in support of exploration missions. The HRP research and technology development is focused on the highest priority risks to crew health and safety with the goal of ensuring mission success and maintaining long-term crew health. Crew health and performance standards, defined by the NASA Chief Health and Medical Officer (CHMO), set the acceptable risk level for exploration missions. The HRP conducts research to inform these standards as well as provide deliverables, such as countermeasures, that ensure standards can be met to maximize human performance and mission success. The Human Health Countermeasures (HHC) Element was formed as part of the HRP to develop a scientifically-based, integrated approach to understanding and mitigating the health risks associated with human spaceflight. These health risks have been organized into four research portfolios that group similar or related risks. A fifth portfolio exists for managing technology developments and infrastructure projects. The HHC Element portfolios consist of: a) Vision and Cardiovascular; b) Exercise and Performance; c) Multisystem; d) Bone; and e) Technology and Infrastructure. The HHC identifies gaps associated with the health risks and plans human physiology research that will result in knowledge required to more fully understand risks and will result in validated countermeasures to mitigate risks.

Norsk, Peter↗
DOE OSTI2020

Attack-resilient algorithms and testbed federation for wide-area protection and control in smart grid

Today’s energy infrastructure is undergoing a massive transformation across all generation, transmission, and distribution systems to provide reliability, efficiency, and sustainability to the power system network. During the past 10 years, there has been a remarkable enhancement in developing close-loop wide-area protection and control (WAPAC) applications, such as automatic generation control (AGC), wide-area protection scheme (WAPS), synchrophasor-based wide-area voltage control system (WAVCS), etc., in the energy management system (EMS) to provide an adequate situational awareness to control center operators during physical disturbances and natural events. The rapid digitalization, unencrypted communication, and numerous data-sharing devices have increased digital access points that have exposed the grid network to countless cyberattacks pertinent to the WAPAC cybersecurity. Given the amount of complex grid network coupled with legacy infrastructures, it is untrustworthy to completely rely on information technology (IT)-based conventional security measures to defend against evolving cyberattacks. Hence, there is a compelling need to go beyond the traditional paradigm of ‘security by obscurity’ and ‘bolt-on’ security measures, and develop a suite of innovative security solutions at multiple layers to transform the current “fault-resilient” grid into “fault and attack-resilient” grid of the future. This dissertation specifically focuses on developing application-specific attack-resilient solutions for critical WAPAC applications in the smart grid. The first part of the study, Attack-Resilient Wide-Area Protection Scheme, presents a cyber-physical attack-resilient system (CPARS) for WAPS, where two anomaly detection methods are proposed to detect multi-level cyberattacks followed by the rules-based intrusion mitigation system (RIMS) to initiate effective mitigation strategies, tailored to these attacks, to restore the normal grid operation after disturbances. The first anomaly detection component, Machine learning-based Anomaly Detection for Centralized WAPS, discusses a novel architecture and methodology for developing a machine-learning-based anomaly detection system (ADS) for the centralized wide-area protection system (CWAPS) by applying the variational mode decomposition (VMD) technique and decision tree (DT) algorithms using cyber logs and synchrophasor measurements. The second component, Multi-Agent-based Anomaly Detection for Decentralized WAPS, presents a two-level hierarchical multi-agent-based decentralized WAPS against the system-aware stealthy cyber-attacks. Finally, for the RIMS, the state transition diagram-based mitigation measures are defined based on the grid operation states and experimental testing and evaluation are presented in a cyber-physical testbed environment. The second part of the study, Attack-Resilient Wide-Area Voltage Control System, addresses the existing vulnerabilities in the wide-area voltage control system (WAVCS), presents the methodology for performing an impact analysis during data integrity attacks, and proposes a data-driven attackresilient system (DARS) by incorporating machine learning-based ADS and rules-based anomaly mitigation system (RAMS) to detect these attacks and provide necessary mitigation actions to maintain the transient voltage stability after disturbances. Finally, the third part, Networked Federation Testbed (NEFTSec) for Smart Grid Cybersecurity, focuses on developing an interconnected federated testbed through a common network like the internet, describes its conceptual architectures, and also presents its design components for experimental testing, validation, and evaluation. Further, it presents the co-simulation interface algorithm (CIA) to facilitate the geographically-dispersed real-time distributed simulation (GD-RTDS) during the cyber-physical federation. In general, this dissertation presents innovative attack-resilient solutions for WAPAC applications that are experimentally tested and evaluated using the PowerCyber testbed and NEFTSec platform to accelerate the transition of state-of-the-art research works to the real-field deployments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2014

Space Radiation and the Challenges Towards Effective Shielding Solutions

The hazards of space radiation and their effective mitigation strategies continue to pose special science and technology challenges to NASA. It is widely accepted now that shielding space vehicles and structures will have to rely on new and innovative materials since aluminum, like all high Z materials, are poor shields against the particulate and highly ionizing nature of space radiation. Shielding solutions, motivated and constrained by power and mass limitations, couple this realization with "multifunctionality," both in design concept as well as in material function and composition. Materials endowed with effective shielding properties as well as with some degree of multi‐functionality may be the kernel of the so‐called "radiation‐smart" structures and designs. This talk will present some of the challenges and potential mitigation ideas towards the realization of such structures and designs.

Barghouty, Abdulnasser↗
NASA NTRS2010

Risk as a Driver for Innovation

The Space Life Sciences directorate (SLSD) and Human Research Program (HRP) at NASA Johnson Space Center has implemented a system for managing human systems risks. These risks are defined as the health and performance risks posed to crew during and after spaceflight. Identification and evaluation of these risks has led to the identification of gaps in knowledge about the risks as well as gaps in technology needed to mitigate them. Traditional routes of closing technology gaps have, in some cases, proven to be too slow when a solution was required quickly. Therefore, certain gaps were used to drive the development of "challenges" for the scientific community. Partnering with open innovation service providers such as InnoCentive and Yet2.com, SLSD and HRP have decreased the amount of time from identification of a need to the evaluation of a solution. Although not all proposed solutions will result in a risk mitigation strategy or tool, the process has allowed faster evaluation of proposed solutions providing the researcher the ability to move to another possible solution if the first does not sufficiently address the problem. Moreover, this process engages the community outside of NASA and broadens the population from which to draw solutions. In the traditional grant funding structure, only those in the specific field will apply for the grant. However, using open innovation, solutions can come from individuals in many different fields. This can expand the general view of a field (way of thinking within a field) and the application of solutions form new fields while providing a pathway for the acquisition of novel solutions or refinements of current mitigations. Identification of the human systems risks has helped drive the development and evaluation of innovative solutions as well as engaging a broader scientific audience in working with NASA.

Davis, Jeff↗
NASA NTRS2011

Method and Apparatus for the Quantification of Particulate Adhesion Forces on Various Substrates

Mitigation strategies for lunar dust adhesion have typically been limited to qualitative analysis. This technical memorandum describes the generation and operation of an adhesion testing device capable of quantitative assessment of adhesion forces between particulates and substrates. An aerosolization technique is described to coat a surface with a monolayer of particulates. Agitation of this surface, via sonication, causes particles to dislodge and be gravitationally fed into an optical particle counter. Experimentally determined adhesion force values are compared to forces calculated from van der Waals interactions and are used to calculate the work of adhesion using Johnson-Kendall-Roberts (JKR) theory. Preliminary results indicate that a reduction in surface energy and available surface area, through topographical modification, improve mitigation of particulate adhesion.

Wohl, Christopher J.↗
DOE OSTI2022

Decoding Golden Eagle Movement Behavior from High-Resolution, Variable-Rate Telemetry Data Through Bayesian Filtering

The recent advances in animal tracking technology have enabled the collection of a vast amount of in situ data regarding the movement of wildlife at high spatiotemporal resolution. These data are usually available at variable time resolutions and contains noise (error) originating from GPS fixes. Decoding movement characteristics, particularly of flying animals, from telemetry data while handling these factors is a challenging yet important task for conservation purposes. Typically, this task is broken into two subtasks: resampling, and model calibration. The resampling subtask converts the variable rate positional data into a constant time interval data, while the model calibration subtask uses the resampled data to tune time-invariant parameters of the proposed models. For telemetry data at high temporal resolutions (order of 1 second), it is very challenging to decouple noise from actual movements using interpolation-based resampling techniques. Any errors introduced during resampling can significantly alter the the calibration and prediction attributes of the movement model. We address this problem through a unified Bayesian state-space framework that can handle both the resampling and calibration tasks in a single step. In addition, we use the speed and heading of the bird from telemetry data to regularize the position information of the bird. We use a Kalman filtering approach to include these nonlinearly related motion parameters within the state space framework. We cross-validated to quantify how this inclusion affects the model performance in estimating true bird movements. The relationship between the true state of the bird and environmental and topographical covariates is then represented parametrically. These parameters are then tuned using stochastic sampling strategies like Markov Chain Monte Carlo (MCMC). We use the telemetry data collected from golden eagles in the western USA to demonstrate the applicability of this approach to build a predictive, probabilistic movement model. Our preliminary results show that this approach provides improved predictive performance in terms of capturing higher-order motion parameters such as angular and horizontal accelerations, which may have simpler and more direct relationships with environmental covariates than corresponding speeds. In this talk, we will demonstrate how this state-space approach benefits the prediction capabilities of a movement model in simulating golden eagle paths through a wind power plant in Wyoming given certain atmospheric conditions. The model outcomes are aimed at informing mitigation strategies that can minimize the potential for collisions of golden eagles with wind turbines.

Bayesian methods↗
DOE OSTI2023

Optimizing foreground mitigation for CMB lensing with combined multifrequency and geometric methods

Here, a key challenge for current and upcoming cosmic microwave background lensing measurements is their sensitivity to biases from extragalactic foregrounds, such as Sunyaev-Zel'dovich signals or cosmic infrared background emission. Several methods have been developed to mitigate these lensing foreground biases, dividing broadly into multifrequency cleaning approaches and modifications to the estimator geometry, but how to optimally combine these methods has not yet been explored in detail. In this paper, we examine which combination of lensing foreground mitigation strategies is best able to reduce the impact of foreground contamination for a Simons Observatory-like experiment while preserving maximal signal-to-noise. Although the optimal combination obtained depends on whether bias reduction or variance reduction is prioritized and on whether polarization data is used, generally, we find that combinations involving both geometric (profile hardening, source hardening, or shear) and multifrequency (symmetric cleaning) methods perform best. For lensing power spectrum measurements from temperature (polarization and temperature), our combined estimator methods are able to reduce the bias below σ/4 or 0.3% (0.1%), a factor of 16 (30) lower than the standard quadratic estimator bias, at a modest signal-to-noise cost of only 18% (12%). In contrast, single-method foreground-mitigation approaches struggle to reduce the bias to a negligible level below σ/2 without incurring a large noise penalty. For upcoming and current experiments, our combined methods therefore represent a promising approach for making lensing measurements with negligible foreground bias.

79 ASTRONOMY AND ASTROPHYSICS↗
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 NTRS2012

Dust-Tolerant Intelligent Electrical Connection System

Faults in wiring systems are a serious concern for the aerospace and aeronautic (commercial, military, and civilian) industries. Circuit failures and vehicle accidents have occurred and have been attributed to faulty wiring created by open and/or short circuits. Often, such circuit failures occur due to vibration during vehicle launch or operation. Therefore, developing non-intrusive fault-tolerant techniques is necessary to detect circuit faults and automatically route signals through alternate recovery paths while the vehicle or lunar surface systems equipment is in operation. Electrical connector concepts combining dust mitigation strategies and cable diagnostic technologies have significant application for lunar and Martian surface systems, as well as for dusty terrestrial applications. The dust-tolerant intelligent electrical connection system has several novel concepts and unique features. It combines intelligent cable diagnostics (health monitoring) and automatic circuit routing capabilities into a dust-tolerant electrical umbilical. It retrofits a clamshell protective dust cover to an existing connector for reduced gravity operation, and features a universal connector housing with three styles of dust protection: inverted cap, rotating cap, and clamshell. It uses a self-healing membrane as a dust barrier for electrical connectors where required, while also combining lotus leaf technology for applications where a dust-resistant coating providing low surface tension is needed to mitigate Van der Waals forces, thereby disallowing dust particle adhesion to connector surfaces. It also permits using a ruggedized iris mechanism with an embedded electrodynamic dust shield as a dust barrier for electrical connectors where required.

Lewis, Mark↗
DOE OSTI2016

Nanostructured Fe-Cr Alloys for Advanced Nuclear Energy Applications

We have completed research on the grain-size stabilization of model nanostructured Fe14Cr base alloys at high temperatures by the addition of non-equilibrium solutes. Fe14Cr base alloys are representative for nuclear reactor applications. The neutron flux in a nuclear reactor will generate He atoms that coalesce to form He bubbles. These can lead to premature failure of the reactor components, limiting their lifetime and increasing the cost and capacity for power generation. In order to mitigate such failures, Fe14Cr base alloys have been processed to contain very small nano-size oxide particles (less than 10 nm in size) that trap He atoms and reduce bubble formation. Theoretical and experimental results indicate that the grain boundaries can also be very effective traps for He atoms and bubble formation. An optimum grain size will be less than 100 nm, ie., nanocrystalline alloys must be used. Powder metallurgy methods based on high-energy ball milling can produce Fe-Cr base nanocrystalline alloys that are suitable for nuclear energy applications. The problem with nanocrystalline alloys is that excess grain-boundary energy will cause grains to grow at higher temperatures and their propensity for He trapping will be lost. The nano-size oxide particles in current generation nuclear alloys provide some grain size stabilization by reducing grain-boundary mobility (Zener pinning – a kinetic effect). However the current mitigation strategy minimizing bubble formation is based primarily on He trapping by nano-size oxide particles. An alternate approach to nanoscale grain size stabilization has been proposed. This is based on the addition of small amounts of atoms that are large compared to the base alloy. At higher temperatures these will diffuse to the grain boundaries and will produce an equilibrium state for the grain size at higher temperatures (thermodynamic stabilization – an equilibrium effect). This would be preferred compared to a kinetic effect, which is not based on an equilibrium state. The PI and coworkers have developed thermodynamic-based models that can be used to select appropriate solute additions to Fe14Cr base alloys to achieve a contribution to grain-size stabilization and He bubble mitigation by the thermodynamic effect. All such models require approximations and the proposed research was aimed at alloy selection, processing and detailed atomic-level microstructure evaluations to establish the efficacy of the thermodynamic effect. The outcome of this research shows that appropriate alloy additions can produce a contribution from the thermodynamic stabilization effect. Furthermore, due to the oxygen typically present in nominally high purity elemental powders used for powder metallurgy processing, the optimum results obtained appeared as a synergistic combination of nano-size oxide particle pinning kinetic effect and the grain-boundary segregation thermodynamic effect.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Review of Quantum Computing Technologies in Power System Optimization

As modern power grids increasingly integrate variable renewable generation, distributed energy resources, and energy storage systems, classical optimization techniques are facing unprecedented challenges. This review examines the emerging application of quantum computing to overcome these challenges in power system optimization, including optimal power flow (OPF), unit commitment (UC), economic dispatch (ED), and intelligent switching and topology optimization (IS-TO). Recent research has introduced various quantum methodologies—such as gate-based, annealing-based, variational algorithms, and quantum-inspired algorithms—to address the combinatorial complexity inherent in grid reconfiguration and energy management. The review summaries the quantum algorithms, quantum devices and the power system test cases, highlighting hybrid quantum–classical strategies that leverage the complementary strengths of both paradigms. Some quantum advantages have been observed, including theoretical speedup, accurate simulation results, scalable qubit usage, efficient QUBO mapping. In particular, the review emphasizes the importance of integrating quantum optimization techniques with classical control frameworks, these hybrid approaches demonstrate the potential to improve real-time grid management and operational reliability. A significant portion of the analysis is devoted to the practical limitations of current quantum devices. Present-day quantum hardware, operating in the noisy intermediate-scale quantum (NISQ) era, remains highly sensitive to noise and limited in qubit connectivity, which constrains the scale and accuracy of implemented algorithms. The review delves into specific challenges such as the need for qubit-efficient encoding techniques and error mitigation strategies that are critical for handling real-world grid optimization problems. In addition, the work draws attention to the performance discrepancies between theoretical quantum speedups and experimental validations, underscoring the importance of rigorous benchmark studies using representative power grid test cases. In summary, this review highlights both the promise and limitations of quantum computing for power system optimization. It provides a comprehensive overview of the state-of-the-art technologies, categorizes recent advancements in algorithm design, and discusses practical considerations for implementation, and serves as an informative resource on current research. Future research directions include developing robust hybrid frameworks, advancing qubit-efficient formulations, and scaling up experimental demonstrations to confirm the theoretical advantages of quantum methods in large-scale power system operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Metrics for Interzonal Dispersion Assessment of Airborne SARS-CoV-2 Within Office Buildings

High ventilation rate is increasingly considered as a mitigation strategy in the rapid spread of COVID-19 in existing buildings in addition to other options like UVGI and added filtration. However, this and other similar measures may also impact energy use and the efficiency of the buildings in which they are installed. Without concrete metrics, the impact of all these potential changes to the system cannot be properly assessed relative to the other impacts the measures might have, including additional energy use, added operation and maintenance costs, and reduced system life. Multizone airflow and contaminant transport simulations involving parameters such as infiltration rate, system configuration, and level of occupancy can provide critical information on relative risk distribution within a building. In this study, prototype airflow models are used to assess the degree to which ventilation-related measures can mitigate the spread of a virus like SARS-CoV-2 in a similar way that prototype energy models are used to study energy efficiency measures. A new detailed medium-sized office building prototype model is developed using the CONTAM software to represent contaminant transport in buildings like those modeled by the U.S. Department of Energy’s detailed medium office prototype model. The goal of this study is to generate a set of suitable metrics that will give a whole-building picture of airborne SARS-CoV-2 virus distributions across the different zones of the building under different parameters and scenarios.

DeGraw, Jason↗
NASA NTRS2023

Compact Lightweight Aerial Sensor System (CLASSy)

In the wake of increasingly intense wildfires, innovative solutions are imperative to enhance wildfire mitigation strategies. Current technological integrations have hit a communicative limit. Between limited flight time, computational expenses as well as financial expenses, there is a hole in the market for an effective, low-tech, and disposable solution. The Compact Lightweight Aerial Sensor System (CLASSy) is designed to revolutionize active disaster operations through comprehensive decision support. CLASSy consists of a lightweight launch mechanism and a flight body equipped with a sensor package and parachute. The assembly integrates sensor networks with data analytics to provide real-time, high-resolution information to incident commanders, directly facilitating decision-making and resource allocation. Infrared imagery and temperature differentials are processed and analyzed throughout flight, offering valuable insights into fire behavior, hotspot detection, and fire spread trajectories. CLASSy is intended to meet a variety of natural disaster mitigation needs through its variable launch height and disposability. CLASSy’s goal is to assist wildfire fighting without taking up any human or material resources. As a result, CLASSy is as lightweight as possible, easily expendable, inexpensive to manufacture, and only requires one operator for effective use. CLASSy’s integrated sensor suite, real-time analytics, and closed loop active communications empower firefighting teams to proactively address wildfire challenges. As the frequency of wildfires continues to rise, technological innovations like CLASSy are crucial to effective wildfire management systems.

Kyleigh Anderson↗
DOE OSTI2021

Janthinobacter additions reduce rotifer grazing of microalga Microchloropsis salina in biotically complex communities

Grazing and parasitism in algal production systems are significant causes of crop loss. Biological control of algal ponds, such as application of protective bacteria, represents a promising alternative to current mitigation strategies. The major barriers to probiotic methods are the lack of identified protective bacteria and uncertainty of scale-up effects, including potential negative interactions with the resident algal microbiome. Here, we report that application of Janthinobacter lividum affords robust protection against rotifer (Brachionus plicatilis) grazing on Microchloropsis salina. Protection was observed at laboratory scale from live bacteria and solvent extract additions as well as in biologically complex communities from bacterial additions to outdoor mesocosms. J. lividum persisted in outdoor communities for at least 3 days following addition, and did not lead to selective exclusion of specific taxa in the resident microbiome. These results demonstrate that J. lividum can provide protection against grazers in these diverse communities, without severe effects on the resident microbiome. Our results suggest that J. lividum is a promising treatment to mitigate algal crop losses due to pests. Additionally, the study highlights the importance of an ecologically-informed approach to algal crop management that will aid future applications in the biological control of algal ponds.

09 BIOMASS FUELS↗
DOE OSTI2021

Modeling potential air temperature reductions yielded by cool roofs and urban irrigation in the Kansas City Metropolitan Area

In this work, we evaluate two mitigation strategies for urban heat island (UHI) in the Kansas City Metropolitan Area (KCMA). Using the Weather Research and Forecasting (WRF) model, we assess the potential benefits of reflective “cool” roofs and urban irrigation on air temperature in typical summer conditions between 2011 and 2015, and during six of the strongest historical heat waves from 2005 to 2016. Under the typical summer conditions, we simulate 2-m air temperature for 10 summer weeks, finding average daytime (07:00–19:00 local time) temperature reductions of 0.08 and 0.28 °C for cool roofs and urban irrigation, respectively. During the six heat-wave episodes, we find daytime temperature reductions of 0.02 and 0.26 °C for the two scenarios, similar to those under typical summer conditions. Our results suggest that urban irrigation can be more efficient than cool roofs in mitigating UHI in metropolitan regions where the majority of the land cover is comprised of areas with low urban (i.e., non-vegetated) fractions. Finally, we find the alteration of surface conditions due to enhanced roof albedos influences precipitation within the WRF simulation, in particular during the heat waves. Further research would be necessary to determine the robustness of this last finding.

54 ENVIRONMENTAL SCIENCES↗