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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Integrated Modeling Driven Evaluation of Opportunities for Climate‐Resilient Perennial Biomass Crop Plantings in Flood‐Prone Agricultural Landscapes

Adapting to future climate change in flood-prone landscapes will require climate-resilient agricultural systems. Planting perennial crops, like switchgrass and willow, along river corridors can mitigate future flooding while supporting bioenergy markets. We developed an integrated assessment linking climate, hydrologic, and inundation model results to assess future flood risk to river-adjacent agricultural lands in the Mid-Atlantic Region (MAR) and explore this opportunity. We produced ensemble streamflow projections for every MAR stream using a hydrologic model driven by a suite of downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 climate projections. We then conducted high-resolution inundation mapping based on projected flood frequencies for baseline and future periods. Results show that in the near-term future, at least two-thirds of the streams will experience 100-year floods more severe than the baseline 200-year floods. Riparian zones are projected to face a median rise of inundation by 9.5%–24.1%. Results show that there is an opportunity to mitigate flooding in over half of MAR's counties with the quantities of switchgrass and willow plantings anticipated for mature bioenergy markets, even under the most extreme (200-year) flood events. Our integrated modeling framework can guide similar regions to evaluate opportunities for flood-resilient agricultural systems under climate change.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Amazon drought resilience – emerging results point to new empirical needs

Will climate change turn tropical forests from a carbon sink to a source (Pan et al., 2011)? Tropical forests cycle more carbon, water, and energy than any other biome (Bonan, 2008). The Amazon is the largest tropical forest, spanning one-third of South America, and any perturbation in its function has repercussions on the global climate. Mild and severe droughts in the Amazon are predicted to double and triple in area, respectively, by 2100, while the area under wet extremes will increase (Duffy et al., 2015). Our understanding of the role of plants' hydrological environments in determining their drought response, however, is limited (Chitra-Tarak et al., 2018, 2021). An important review by Costa et al. (2023; pp. 714–733) published in this issue of New Phytologist highlights that shallow-water table (WT) forests constitute c. 50% of the Amazon and may act as hydrological refugia during droughts, yet they have been neglected in Amazon forest research to date. Emerging results suggest that the shallow-WT forests that dominate the Amazon basin may increase in productivity under moderate droughts due to relief from hypoxia, suggesting a potential buffer from drought relative to deeper WT forests (Fig. 1). During severe droughts, however, shallow-WT forests may be vulnerable to collapse due to drought-intolerant traits. Addressing the underrepresentation of relatively drought-resilient shallow-WT forests in the Amazon's forest inventories may help resolve the much-debated incongruence in recent studies of the Amazon's drought resilience. Data from forest inventories (biased toward deep-WT forests) indicate that the Amazon's carbon sink is declining, partially because of drought impacts (Phillips et al., 2009; Brienen et al., 2015), whereas basin-wide satellite-based measures of gross primary productivity, which include shallow-WT forests, indicate varied regional responses to droughts (Saleska et al., 2007; Brando et al., 2010). Costa et al.'s (2023) descriptive insights of the intricate balance of geology, topography, hydrology, vegetation, and drought on ecosystem function, as well as their conceptual predictive framework, are useful for developing new empirical research in these understudied ecosystems and improving Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modifying the Asynchronous Jacobi Method for Data Corruption Resilience

Moving scientific computation from high-performance computing (HPC) and cloud computing (CC) environments to devices on the edge, i.e., physically near instruments of interest, has received tremendous interest in recent years. Such edge computing environments can operate on data in situ, offering enticing benefits over data aggregation to HPC and CC facilities that include avoiding costs of transmission, increased data privacy, and real-time data analysis. Because of the inherent unreliability of edge computing environments, new fault-tolerant approaches must be developed before the benefits of edge computing can be realized. Motivated by algorithm-based fault tolerance, a variant of the asynchronous Jacobi (ASJ) method is developed that achieves resilience to data corruption by rejecting solution approximations from neighbor devices according to a bound derived from convergence theory. Numerical results on a two-dimensional Poisson problem show that the new rejection criterion, along with a novel approximation to the shortest path length on which the criterion depends, restores convergence for the ASJ variant in the presence of certain types data corruption. Numerical results are obtained for when the singular values in the analytic bound are approximated. Additional linear systems are also explored, one with a more dense sparsity pattern and one that includes advection. All results indicate that successful resilience to data corruption depends on whether the bound tightens fast enough to reject corrupted data before the iteration evolution deviates significantly from that predicted by the convergence theory defining the bound. This observation generalizes to future work on algorithm-based fault tolerance for other asynchronous algorithms, including upcoming approaches that leverage Krylov subspaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Zaccai neutron resilience and site-specific hydration dynamics in a globular protein

A discussion is presented of contributions of the Zaccai group to the understanding of flexibility in biological macromolecules using dynamic neutron scattering. The concept of resilience as introduced by Zaccai is discussed and investigated using molecular dynamics simulation on camphor-bound cytochrome P450. The resilience of hydrophilic residues is found to be more strongly affected by hydration than that of hydrophobic counterparts. The hydration-induced softening of protein propagates from the surface into the dry core. Furthermore, buried hydrophilic residues behave more like those exposed on the protein surface, and are different from their hydrophobic counterparts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Noise-Resilient and Reduced Depth Approximate Adders for NISQ Quantum Computing

The "Noisy intermediate-scale quantum" NISQ machine era primarily focuses on mitigating noise, controlling errors, and executing high-fidelity operations, hence requiring shallow circuit depth and noise robustness. Approximate computing is a novel computing paradigm that produces imprecise results by relaxing the need for fully precise output for error-tolerant applications including multimedia, data mining, and image processing. We investigate how approximate computing can improve the noise resilience of quantum adder circuits in NISQ quantum computing. We propose five designs of approximate quantum adders to reduce depth while making them noise-resilient, in which three designs are with carryout, while two are without carryout. We have used novel design approaches that include approximating the Sum only from the inputs (pass-through designs) and having zero depth, as they need no quantum gates. The second design style uses a single CNOT gate to approximate the SUM with a constant depth of O(1). We performed our experimentation on IBM Qiskit on noise models including thermal, depolarizing, amplitude damping, phase damping, and bitflip: (i) Compared to exact quantum ripple carry adder without carryout the proposed approximate adders without carryout have improved fidelity ranging from 8.34% to 219.22%, and (ii) Compared to exact quantum ripple carry adder with carryout the proposed approximate adders with carryout have improved fidelity ranging from 8.23% to 371%. Further, the proposed approximate quantum adders are evaluated in terms of various error metrics.

Gaur, Bhaskar↗
DOE OSTI2016

Multi Infrastructure Control and Optimization Toolkit, Resilient Design Module (MICOT-RDT), version 2.X

MICOT is a tool for optimizing and controlling infrastructure systems. In includes modules for optimizing the operations of an infrastructure structure (for example optimal dispatch), designing infrastructure systems, restoring infrastructures systems, resiliency, preparing for natural disasters, interdicting networks, state estimation, sensor placement, and simulation of infrastructure systems. It implements algorithms developed at LANL that have been published in the academic community. This is a release of the of resilient design module of the MICOT.

Bent, Russell↗
DOE OSTI2020

Power Distribution Designing For Resilience Application (powdder)

Power Distribution Designing for Resilience Application (PowDDeR) is a software application to succinctly capture the capabilities of a power system to respond to disturbances, including natural or human (malicious or errors) caused disturbances. The software provides a measure of resilience for power systems.

McJunkin, TimothyR↗
DOE OSTI2021

Linking resource availability to pantropical forest canopy resistance and resilience to cyclone disturbance

Statement of purpose: Tropical cyclones are intensifying and occurring at higher latitudes in recent decades, but the mechanisms underpinning the resistance (ability to withstand disturbance-induced change) and resilience (pace of return to pre-disturbance reference values) of tropical forests to cyclones remains largely unexplored at the pantropical scale. We conducted a meta-analysis to investigate the role of soil resource availability (i.e., total soil phosphorus concentration) in mediating site-level forest canopy resistance and resilience to cyclones pan-tropically. We evaluated cyclone-induced and post-cyclone litterfall mass (g/m2/day), phosphorus (P) and nitrogen (N) fluxes (mg/m2/day), as well as concentrations (mg/g) across 73 case studies in Australia, Guadeloupe, Hawaii, Mexico, Puerto Rico, and Taiwan. The dataset zip file includes three data and two metadata files: - The compiled Litterfall Mass Flux data from tropical forests across the globe prior to and after varying tropical cyclone disturbances are provided in Litterfall_Mass.csv. This data file also includes site location, geographical characteristics, elevation, soil phosphorus concentration, geology, and several variables related to each tropical cyclone disturbance. - The compiled Litterfall Nitrogen and Phosphorus Flux data from tropical forests across the globe prior to and after varying tropical cyclone disturbances are provided in Litterfall_Nutrients.csv. This data file also includes site location, geographical characteristics, elevation, soil phosphorus concentration, geology, and several variables related to each tropical cyclone disturbance. - Tropical cyclone track data compiled from HURDAT2 and IBTrACS databases and used as input in the HURRECON model (https://github.com/hurrecon-model/HurreconR) to generate wind data is provided in hurdat2-1851-2019-052520.txt. - The metadata file (Metadata_Meta-analysis_Litterfall-Mass.pdf) has the complete information on each variable included in the Litterfall_Mass.csv dataset, the data sources, and data processing information. - The metadata file (Metadata_Meta-analysis_Litterfall-Nutrients.pdf) has the complete information on each variable included in the Litterfall_Nutrients.csv dataset, the data sources, and data processing information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

A simulation infrastructure for examining the performance of resilience strategies at scale

Fault-tolerance is a major challenge for many current and future extreme-scale systems, with many studies showing it to be the key limiter to application scalability. While there are a number of studies investigating the performance of various resilience mechanisms, these are typically limited to scales orders of magnitude smaller than expected for next-generation systems and simple benchmark problems. In this paper we show how, with very minor changes, a previously published and validated simulation framework for investigating application performance of OS noise can be used to simulate the overheads of various resilience mechanisms at scale. Using this framework, we compare the failure-free performance of this simulator against an analytic model to validate its performance and demonstrate its ability to simulate the performance of two popular rollback recovery methods on traces from real.

Ferreira, Kurt Brian↗
DOE OSTI2013

LEDS Global Partnership in Action: Advancing Climate-Resilient Low Emission Development Around the World [Fact Sheet]

Many countries around the globe are designing and implementing low emission development strategies (LEDS). These LEDS seek to achieve social, economic, and environmental development goals while reducing long-term greenhouse gas (GHG) emissions and increasing resiliency to climate change impacts. The LEDS Global Partnership (LEDS GP) harnesses the collective knowledge and resources of more than 120 countries and international donor and technical organizations to strengthen climate-resilient low emission development efforts around the world.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Resilient Power Systems

The goals of this seminar are to: introduce some resiliency concepts; introduce a problem for improving resilience; and review and introduce some high-level optimization concepts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Next-generation Algorithms for Assessing Infrastructure Vulnerability and Optimizing System Resilience

This report summarizes the work performed under the project project Next-Generation Algorithms for Assessing Infrastructure Vulnerability and Optimizing System Resilience. The goal of the project was to improve mathematical programming-based optimization technology for infrastructure protection. In general, the owner of a network wishes to design a network a network that can perform well when certain transportation channels are inhibited (e.g. destroyed) by an adversary. These are typically bi-level problems where the owner designs a system, an adversary optimally attacks it, and then the owner can recover by optimally using the remaining network. This project funded three years of Deon Burchett's graduate research. Deon's graduate advisor, Professor Jean-Philippe Richard, and his Sandia advisors, Richard Chen and Cynthia Phillips, supported Deon on other funds or volunteer time. This report is, therefore. essentially a replication of the Ph.D. dissertation it funded in a format required for project documentation. The thesis had some general polyhedral research. This is the study of the structure of the feasible region of mathematical programs, such as integer programs. For example, an integer program optimizes a linear objective function subject to linear constraints, and (nonlinear) integrality constraints on the variables. The feasible region without the integrality constraints is a convex polygon. Careful study of additional valid constraints can significantly improve computational performance. Here is the abstract from the dissertation: We perform a polyhedral study of a multi-commodity generalization of variable upper bound flow models. In particular, we establish some relations between facets of single- and multi- commodity models. We then introduce a new family of inequalities, which generalizes traditional flow cover inequalities to the multi-commodity context. We present encouraging numerical results. We also consider the directed edge-failure resilient network design problem (DRNDP). This problem entails the design of a directed multi-commodity flow network that is capable of fulfilling a specified percentage of demands in the event that any G arcs are destroyed, where G is a constant parameter. We present a formulation of DRNDP and solve it in a branch-column-cut framework. We present computational results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Using Simulation to Evaluate the Performance of Resilience Strategies and Process Failures

Fault-tolerance has been identified as a major challenge for future extreme-scale systems. Current predictions suggest that, as systems grow in size, failures will occur more frequently. Because increases in failure frequency reduce the performance and scalability of these systems, significant effort has been devoted to developing and refining resilience mechanisms to mitigate the impact of failures. However, effective evaluation of these mechanisms has been challenging. Current systems are smaller and have significantly different architectural features (e.g., interconnect, persistent storage) than we expect to see in next-generation systems. To overcome these challenges, we propose the use of simulation. Simulation has been shown to be an effective tool for investigating performance characteristics of applications on future systems. In this work, we: identify the set of system characteristics that are necessary for accurate performance prediction of resilience mechanisms for HPC systems and applications; demonstrate how these system characteristics can be incorporated into an existing large-scale simulator; and evaluate the predictive performance of our modified simulator. We also describe how we were able to optimize the simulator for large temporal and spatial scales-allowing the simulator to run 4x faster and use over 100x less memory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Vulnerability Assessments and Resilience Planning at Federal Facilities. Preliminary Synthesis of Project

U.S. government agencies are now directed to assess the vulnerability of their operations and facilities to climate change and to develop adaptation plans to increase their resilience. Specific guidance on methods is still evolving based on the many different available frameworks. Agencies have been experimenting with these frameworks and approaches. This technical paper synthesizes lessons and insights from a series of research case studies conducted by the investigators at facilities of the U.S. Department of Energy and the Department of Defense. The purpose of the paper is to solicit comments and feedback from interested program managers and analysts before final conclusions are published. The paper describes the characteristics of a systematic process for prioritizing needs for adaptation planning at individual facilities and examines requirements and methods needed. It then suggests a framework of steps for vulnerability assessments at Federal facilities and elaborates on three sets of methods required for assessments, regardless of the detailed framework used. In a concluding section, the paper suggests a roadmap to further develop methods to support agencies in preparing for climate change. The case studies point to several preliminary conclusions; (1) Vulnerability assessments are needed to translate potential changes in climate exposure to estimates of impacts and evaluation of their significance for operations and mission attainment, in other words into information that is related to and useful in ongoing planning, management, and decision-making processes; (2) To increase the relevance and utility of vulnerability assessments to site personnel, the assessment process needs to emphasize the characteristics of the site infrastructure, not just climate change; (3) A multi-tiered framework that includes screening, vulnerability assessments at the most vulnerable installations, and adaptation design will efficiently target high-risk sites and infrastructure; (4) Vulnerability assessments can be connected to efforts to improve facility resilience to motivate participation; and (5) Efficient, scalable methods for vulnerability assessment can be developed, but additional case studies and evaluation are required.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Evaluating Proposed Investments in Power System Reliability and Resilience: Preliminary Results from Interviews with Public Utility Commission Staff

Policymakers and regulatory agencies are expressing renewed interest in the reliability and resilience of the U.S. electric power system in large part due to growing recognition of the challenges posed by climate change, extreme weather events, and other emerging threats. Unfortunately, there has been little or no consolidated information in the public domain describing how public utility/service commission (PUC) staff evaluate the economics of proposed investments in the resilience of the power system. Having more consolidated information would give policymakers a better understanding of how different state regulatory entities across the U.S. make economic decisions pertaining to reliability/resiliency. To help address this, Lawrence Berkeley National Laboratory (LBNL) was tasked by the U.S. Department of Energy Office of Energy Policy and Systems Analysis (EPSA) to conduct an initial set of interviews with PUC staff to learn more about how proposed utility investments in reliability/resilience are being evaluated from an economics perspective. LBNL conducted structured interviews in late May-early June 2016 with staff from the following PUCs: Washington D.C. (DCPSC), Florida (FPSC), and California (CPUC).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Front-Line Resilience Perspectives: The Electric Grid

This report seeks to summarize how states and local utility companies are approaching all-hazards resilience in planning, construction, operations, and maintenance of the electric system, as well as challenges faced when addressing all-hazards resilience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Material Resilience in Harsh Service Conditions

Resilience describes the attributes of a material that allow it to withstand or resist detrimental environmental effects degrading properties and performance. In service, materials may experience harsh or extreme conditions, but even modest thermal or load conditions experienced over a long period can degrade performance. Thus, the National Nuclear Security Administration mission requires predictive understanding of materials performance in harsh and extreme conditions over long periods. This is particularly true for applications in which replacement is impractical, impossible, or costly. This area of leadership addresses the evolution of material properties in environments that include static and dynamic stress, radiation, and chemical or thermal extremes. A particular focus is on situations when environments coexist or for which collection of experimental data is challenging or impossible. The capability to predict and control the nature and evolution of properties to allow designing resilience is a crucial aspect of mission success in national nuclear, global, and energy security.

36 MATERIALS SCIENCE↗