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Results for “Resilience Modeling”

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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Natural variation in growth and yield to waterlogging across climate-diverse pennycress accessions

Many winter annual crops, such as pennycress ( Thlaspi arvense L.), are subjected to heavy precipitation events during their growing season. Therefore, it is essential to identify pennycress accessions with natural variation in flooding resilience. We used climate modeling data to assess spring soil moisture levels in the geographic origins of 471 natural pennycress accessions. We selected 34 accessions with variation in predicted soil moisture and tested survivability under prolonged waterlogging at the rosette stage. It took seven weeks for the first accessions to die, indicating that pennycress is hardy to prolonged waterlogging at the vegetative stage. Furthermore, we chose ‘susceptible’ and ‘tolerant’ accessions to waterlog for one week at the reproductive stage, the growth stage aligned with spring rainfall. Six accessions had significantly reduced seed weight at maturity and two had minimal impacts on growth and seed yield after waterlogging and can be further explored for adaptive traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Feedstock variability impacts the bioconversion of sugar and lignin streams derived from corn stover by Clostridium tyrobutyricum and engineered Pseudomonas putida

Abstract Feedstock variability represents a challenge in lignocellulosic biorefineries, as it can influence both lignocellulose deconstruction and microbial conversion processes for biofuels and biochemicals production. The impact of feedstock variability on microbial performance remains underexplored, and predictive tools for microbial behaviour are needed to mitigate risks in biorefinery scale‐up. Here, twelve batches of corn stover were deconstructed via deacetylation, mechanical refining, and enzymatic hydrolysis to generate lignin‐rich and sugar streams. These batches and their derived streams were characterised to identify their chemical components, and the streams were used as substrates for producing muconate and butyrate by engineered Pseudomonas putida and wildtype Clostridium tyrobutyricum , respectively. Bacterial performance (growth, product titers, yields, and productivities) differed among the batches, but no strong correlations were identified between feedstock composition and performance. To provide metabolic insights into the origin of these differences, we evaluated the effect of twenty‐three isolated chemical components on these microbes, including three components in relevant bioprocess settings in bioreactors, and we found that growth‐inhibitory concentrations were outside the ranges observed in the streams. Overall, this study generates a foundational dataset on P. putida and C. tyrobutyricum performance to enable future predictive models and underscores their resilience in effectively converting fluctuating lignocellulose‐derived streams into bioproducts.

09 BIOMASS FUELS↗
DOE OSTI2020

Convergent evolution of tree hydraulic traits in Amazonian habitats: implications for community assemblage and vulnerability to drought

Amazonian droughts are increasing in frequency and severity. However, little is known about how this may influence species-specific vulnerability to drought across different ecosystem types. We measured 16 functional traits for 16 congeneric species from six families and eight genera restricted to floodplain, swamp, white-sand or plateau forests of Central Amazonia. We investigated whether habitat distributions can be explained by species hydraulic strategies, and if habitat specialists differ in their vulnerability to embolism that would make water transport difficult during drought periods. We found strong functional differences among species. Nonflooded species had higher wood specific gravity and lower stomatal density, whereas flooded species had wider vessels, and higher leaf and xylem hydraulic conductivity. The P 50 values (water potential at 50% loss of hydraulic conductivity) of nonflooded species were significantly more negative than flooded species. However, we found no differences in hydraulic safety margin among species, suggesting that all trees may be equally likely to experience hydraulic failure during severe droughts. Water availability imposes a strong selection leading to differentiation of plant hydraulic strategies among species and may underlie patterns of adaptive radiation in many tropical tree genera. Our results have important implications for modeling species distribution and resilience under future climate scenarios.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The circular bioeconomy: a driver for system integration

Background: Human and earth system modeling, traditionally centered on the interplay between the energy system and the atmosphere, are facing a paradigm shift. The Intergovernmental Panel on Climate Change’s mandate for comprehensive, cross-sectoral climate action emphasizes avoiding the vulnerabilities of narrow sectoral approaches. Our study explores the circular bioeconomy, highlighting the intricate interconnections among agriculture, forestry, aquaculture, technological advancements, and ecological recycling. Collectively, these sectors play a pivotal role in supplying essential resources to meet the food, material, and energy needs of a growing global population. We pose the pertinent question of what it takes to integrate these multifaceted sectors into a new era of holistic systems thinking and planning. Results: The foundation for discussion is provided by a novel graphical representation encompassing statistical data on food, materials, energy flows, and circularity. This representation aids in constructing an inventory of technological advancements and climate actions that have the potential to significantly reshape the structure and scale of the economic metabolism in the coming decades. In this context, the three dominant mega-trends—population dynamics, economic developments, and the climate crisis—compel us to address the potential consequences of the identified actions, all of which fall under the four categories of substitution, efficiency, sufficiency, and reliability measures. Substitution and efficiency measures currently dominate systems modeling. Including novel bio-based processes and circularity aspects might require only expanded system boundaries. Conversely, paradigm shifts in systems engineering are expected to center on sufficiency and reliability actions. Effectively assessing the impact of sufficiency measures will necessitate substantial progress in inter- and transdisciplinary collaboration, primarily due to their non-technological nature. In addition, placing emphasis on modeling the reliability and resilience of transformation pathways represents a distinct and emerging frontier that highlights the significance of an integrated network of networks. Conclusions: Existing and emerging circular bioeconomy practices can serve as prime examples of system integration. These practices facilitate the interconnection of complex biomass supply chain networks with other networks encompassing feedstock-independent renewable power, hydrogen, CO 2 , water, and other biotic, abiotic, and intangible resources. Elevating the prominence of these connectors will empower policymakers to steer the amplification of synergies and mitigation of tradeoffs among systems, sectors, and goals.

09 BIOMASS FUELS↗
DOE OSTI2026

Oakland University Cybersecurity Center (Final Scientific/Technical Report)

This report summarizes the outcomes of Award DE-CR0000023, “Oakland University Cybersecurity Center,” a 31-month project funded by the U.S. Department of Energy Office of Cybersecurity, Energy Security, and Emergency Response (CESER). The project addressed cybersecurity risks facing small and medium-sized manufacturers (SMMs) transitioning to Industry 4.0. The project integrated customer discovery, applied research, and cybersecurity training development. A total of 51 cybersecurity assessments identified significant gaps in baseline practices, incident response, and workforce capability. Research efforts produced a scalable mitigation framework tailored to SMM environments, and workforce analysis identified persistent talent gaps. Eight cybersecurity training modules were developed and deployed via Oakland University’s Professional and Continuing Education (PACE) platform. All objectives were completed, with 98.93% federal budget utilization and cost share exceeding requirements. The project establishes a scalable model for strengthening cybersecurity resilience and workforce capacity across U.S. manufacturing supply chains.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Framework for Modeling 3D-Printed Concrete Construction to Assess Energy Efficiency and Backup Power Trade-Offs in a Mixed-Use, New Construction Neighborhood Development

This paper presents a framework that expands the URBANopt(TM) modeling platform to include 3D-printed concrete wall assemblies and assess energy efficiency and backup power trade-offs in new housing developments. Applied to a planned mixed-use neighborhood in Oil City, Pennsylvania, the workflow integrates building energy and distributed energy resource (DER) modeling to evaluate envelope and equipment upgrades alongside DER operations. Results show that advanced 3D-printed envelopes combined with efficient systems and onsite photovoltaics (PV) and storage reduce energy use intensity and sustain critical loads during outages. The framework supports planning for emerging construction technologies by quantifying key trade-offs between energy efficiency and backup power performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2004

High Temperature Propulsion System Structural Seals for Future Space Launch Vehicles

Durable, flexible sliding seals are required in advanced hypersonic engines to seal the perimeters of movable engine ramps for efficient, safe operation in high heat flux environments at temperatures of 2000 to 2500 F. Current seal designs do not meet the demanding requirements for future engines, so NASA s Glenn Research Center is developing advanced seals and preloading devices to overcome these shortfalls. An advanced ceramic wafer seal design and two types of seal preloading devices were evaluated in a series of compression, scrub, and flow tests. Silicon nitride wafer seals survived 2000 in. 1000 cycles) of scrubbing at 1600 F against an Inconel 625 rub surface with no chips or signs of damage. Flow rates measured for the wafers before and after scrubbing were almost identical and were up to 32 times lower than those recorded for the best braided rope seal flow blockers. Canted coil springs and silicon nitride compression springs showed promise conceptually as potential seal preloading devices to help maintain seal resiliency. A finite element model of the canted coil spring revealed that it should be possible to produce a spring out of high temperature materials for applications at 2000+ F.

Dunlap, Patrick H., Jr.↗
NASA NTRS2003

High Temperature Propulsion System Structural Seals for Future Space Launch Vehicles

Durable, flexible sliding seals are required in advanced hypersonic engines to seal the perimeters of movable engine ramps for efficient, safe operation in high heat flux environments at temperatures of 2000 to 2500 F. Current seal designs do not meet the demanding requirements for future engines, so NASA's Glenn Research Center is developing advanced seals and preloading devices to overcome these shortfalls. An advanced ceramic wafer seal design and two types of seal preloading devices were evaluated in a series of compression, scrub, and flow tests. Silicon nitride wafer seals survived 2000 in. (1000 cycles) of scrubbing at room temperature against an Inconel 625 rub surface with no chips or signs of damage. Flow rates measured for the wafers before and after scrubbing were almost identical and were much lower than those recorded for the best braided rope seal flow blockers. Canted coil springs and silicon nitride compression springs showed promise conceptually as potential seal preloading devices to help maintain seal resiliency. A finite element model of the canted coil spring revealed that it should be possible to produce a spring out of high temperature materials for applications at 2000+ F.

Dunlap, Patrick H., Jr.↗
NASA NTRS2017

Identification of Novel Desiccation-Tolerant S. cerevisiae Strains for Deep Space Biosensors

NASA's BioSentinel mission, a secondary payload that will fly on the Space Launch System's first Exploration Mission (EM-1), utilizes the budding yeast S. cerevisiae to study the biological response to the deep space radiation environment. Yeast samples are desiccated prior to launch to suspend growth and metabolism while the spacecraft travels to its target heliocentric orbit beyond Low Earth Orbit. Each sample is then rehydrated at the desired time points to reactivate the cells. A major risk in this mission is the loss of cell viability that occurs in the recovery period following the desiccation and rehydration process. Cell survival is essential for the detection of the biological response to features in the deep space environment, including ionizing radiation. The aim of this study is to mitigate viable cell loss in future biosensors by identifying mutations and genes that confer tolerance to desiccation stress in rad51, a radiation-sensitive yeast strain. We initiated a screen for desiccation-tolerance after rehydrating cells that were desiccated for three years, and selected various clones exhibiting robust growth. To verify retention of radiation sensitivity in the isolated clones - a crucial feature for a successful biosensor - we exposed them to ionizing radiation. Finally, to elucidate the genetic and molecular bases for observed desiccation-tolerance, we will perform whole-genome sequencing of those rad51 clones that exhibit both robust growth and radiation sensitivity following desiccation. The identification and characterization of desiccation-tolerant strains will allow us to engineer a biological model that will be resilient in face of the challenges of the deep space environment, and will thus ensure the experimental success of future biosensor missions.

S. cerevisiae↗
NASA NTRS2017

Identification of Novel Desiccation-Tolerant S. cerevisiae Strains for Deep Space Biosensors

NASA's BioSentinel mission, a secondary payload that will fly on the Space Launch Systems first Exploration Mission (EM-1), utilizes the budding yeast S. cerevisiae to study the biological response to the deep space radiation environment. Yeast samples are desiccated prior to launch to suspend growth and metabolism while the spacecraft travels to its target heliocentric orbit beyond Low Earth Orbit. Each sample is then rehydrated at the desired time points to reactivate the cells. A major risk in this mission is the loss of cell viability that occurs in the recovery period following the desiccation and rehydration process. Cell survival is essential for the detection of the biological response to features in the deep space environment, including ionizing radiation.The aim of this study is to mitigate viable cell loss in future biosensors by identifying mutations and genes that confer tolerance to desiccation stress in rad51, a radiation-sensitive yeast strain. We initiated a screen for desiccation-tolerance after rehydrating cells that were desiccated for three years, and selected various clones exhibiting robust growth. To verify retention of radiation sensitivity in the isolated clonesa crucial feature for a successful biosensorwe exposed them to ionizing radiation. Finally, to elucidate the genetic and molecular bases for observed desiccation-tolerance, we will perform whole-genome sequencing of those rad51 clones that exhibit both robust growth and radiation sensitivity following desiccation. The identification and characterization of desiccation-tolerant strains will allow us to engineer a biological model that will be resilient in face of the challenges of the deep space environment, and will thus ensure the experimental success of future biosensor missions.

S. cerevisiae↗
NASA NTRS2018

Enhancing New York City's Resilience to Sea Level Rise and Increased Coastal Flooding

The large population and major economic assets along New York City's extensive waterfront face exposure to sea level rise (SLR) and coastal flooding. The New York City Panel on Climate Change (NPCC), an advisory group of academic and private-sector experts, provides the city with scientific guidance on future climate risks. Here we highlight current NPCC research on sea level rise, coastal flooding, with some of the City's current and planned responses.Twentieth century SLR in New York City (2.8 cm/decade) exceeded the global average (1.2-1.9 cm/decade), underscoring a greater regional risk. In 2015, the NPCC projected a 2080s SLR of 46-99 cm relative to 2000-2004 (25th -75th percentile) at the Battery, with high-end SLR estimates (90th percentile) of 1.9 m by 2100. Growing evidence of potential instability of the West Antarctic Ice Sheet (WAIS) suggests the possibility of even higher future sea levels. We therefore present a new low probability, yet high impact SLR scenario for New York City, which incorporates these ice sheet instabilities. The new SLR projections will be combined with coastal flood return period curves for the 100-year storm flood levels. Related ongoing research examines changes in storm characteristics, surge--sea level rise interactions, and mapping of neighborhoods at risk.Guided by NPCC findings, New York City undertakes programs to strengthen coastal defenses, tailored to specific neighborhood needs. NPCC in collaboration with the city, continues to investigate vulnerability to extreme climate events, such as inland floods and coastal storms, and to develop stronger links with community-based stakeholder groups. New York City's plans to enhance coastal urban resiliency stand as a model for other urban coastal centers as they prepare for climate change.

Gornitz, Vivien↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗
DOE OSTI2021

The Role of Hydropower in the Next-Generation Grid

Hydropower can provide a low-carbon source of energy, capacity, and flexibility to the grid. The National Renewable Energy Laboratory's (NREL's) hydropower research covers multiple aspects of grid integration, including hydropower's role in grid planning, operations modeling, and reliability and resilience research.

grid integration↗
DOE OSTI2022

Controlled Environment Agriculture - Farming and Food Access for Healthy Diets

Fruits and vegetables are critical for a healthy diet and USDA guidelines recommend increasing fruit and vegetable consumption for almost all Americans. However, most food system lifecycle assessments do not capture the importance of these food groups in the food system. Moreover, long supply chains and limited access to fresh produce are particularly prevalent in disadvantaged neighborhoods. Many of these communities are food deserts or food swamps characterized by a lack of full-scale groceries, and a prevalence of convenience stores and fast-food restaurants. Stocking of fresh produce is difficult and often unprofitable for small stores. Convenience stores are usually space-limited, unable to achieve economies-of-scale in purchasing and have difficulty managing the short shelf-life of fresh produce. Controlled-Environment (CE) farming, including greenhouses and fully indoor vertical farms, have the potential to address persistent food access issues for disadvantaged communities. CE farming offers several potential advantages for food desert and food swamp neighborhoods, including shorter or non-existent transport distances and fewer middlemen, which could reduce costs. CE farming can be integrated into existing buildings at virtually any scale, providing local jobs and revitalization of community hubs such as shopping malls, or larger-scale farms located in close-in warehouse or industrial areas. Rainwater harvesting and recovery of nutrients from wastewater could further improve food system resilience and circularity. Geospatial modeling of CE farming in case study cities of various sizes and densities will help to quantify the benefits of CE farming. Geospatial modeling can help to answer questions such as whether sufficient collection area is available for rainwater harvesting for a CE farm, and what size of farm would be required to serve the community living within walking distance of the farm. This paper reports on progress in geospatial modeling of CE farming integration into several case study cities.

controlled environment agriculture↗
DOE OSTI2021

Historical Contingency in Microbial Resilience to Hydrologic Perturbations

Development of reliable biogeochemical models requires a mechanistic consideration of microbial interactions with hydrology. Microbial response to and its recovery after hydrologic perturbations (i.e., resilience) is a critical component to understand in this regard, but generally difficult to predict because the impacts of future events can be dependent on the history of perturbations (i.e., historical contingency). Fundamental issues underlying this phenomenon include how microbial resilience to hydrologic perturbations is influenced by historical contingency and how their relationships vary depending on the characteristics of microbial functions. To answer these questions, we considered a simple microbial community composed of two species that redundantly consume a common substrate but specialize in producing distinct products and developed a continuous flow reactor model where the two species grow with trade-offs along the flow rate. Simulations of this model revealed that (1) the history of hydrologic perturbations can lead to the shifts in microbial populations, which consequently affect the community's functional dynamics, and (2) while historical contingency in resilience was consistently predicted for all microbial functions, it was more pronounced for specialized functions, compared to the redundant function. As a signature of historical contingency, our model also predicted the emergence of hysteresis in the transitions across conditions, a critical aspect that can affect transient formation of intermediate compounds in biogeochemistry. This work presents microbial growth traits and their functional redundancy or specialization as fundamental factors that control historical contingencies in resilience.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

How Can Construction Process Simulation Modeling Aid the Integration of Lean Principles in the Factory-Built Housing Industry?

New and existing factories that produce and deliver factory-built housing can benefit from construction process simulation modeling to explore the integration of Lean principles in their operations. Construction process simulation modeling provides digital or virtual recreations of the real-world factory environments to visualize, quantify, analyze, and optimize their underlying behavior, including factory productivity, material flow, labor dynamics, bottlenecks, and work scope. One of the key benefits of process simulation modeling is the ability to create and compare "what-if" scenarios, including integrating Lean principles such as reducing waste (for example, transportation, waiting), line balancing, and just-in-time concepts. In general, three process simulation methods are widely used: discrete event simulation (DES), agentbased modeling (ABM), and system dynamics (SD). Myriad process simulation software also is available, but depending on the industry, complexity of the system, and purposes of the simulation, some software might be more appropriate. Similar to how computer-aided design (CAD) software such as AutoCAD and Rhinoceros enable building design of modular or factory-built housing, process simulation modeling software such as jStrobe, ProModel, and AnyLogic can enable factory design of new and existing factories to deliver modular affordable housing at scale, as opposed to traditional site-built construction. Software with DES capabilities can help generate a process model that is a logical representation of resources and activities in a factory. Software with CAD-DES integration can leverage product-process data integration to help spatially visualize a DES model of the factory in the CAD environment. Software with multimethod simulation capabilities, widely used in the manufacturing industry, brings together DES, ABM, and SD in a single platform that allows visualization, quantification, analyses, and optimization at varying data fidelities. Near-real-time data from an existing factory can be directly plugged into multimethod simulation software so that the construction process simulation model is a near-accurate representation of the real-world factory conditions. This report provides insights into the use of simulation as an aid to integrate Lean concepts in factories, including guidelines for selecting the appropriate process simulation modeling method and software. These insights have been developed as part of ongoing process simulation modeling research, development, and demonstration projects at the U.S. Department of Housing and Urban Development, the U.S. Department of Energy, and the National Renewable Energy Laboratory focused on how process simulation models can enable better integration of resilience, energy efficiency, and low-carbon design strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Risk-controlled Expansion Planning with Distributed Resources (REPAIR) v1.0

The Risk-controlled Expansion Planning with Distributed Resources (REPAIR) is an innovative tool to support decisions around utility grid planning to prevent and mitigate the impact of outages caused by routine equipment failures (reliability) or by extreme events (resilience), such as storms, earthquakes or wildfires that long term interruption of service. REPAIR is a risk-based optimization and decision-making model allowing informed and transparent "cost vs risk" decisions regarding infrastructural planning of electric utilities. The model considers long-term resilience and reliability planning strategies that rely on traditional infrastructure upgrade (e.g. circuit hardening, reinforcement, new substations, etc.) or new investment alternatives, such as DERs.

Heleno, Miguel [Lawrence Berkeley National Laborat↗