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DOE OSTI2014

A critical analysis of hazard resilience measures within sustainability assessment frameworks

Today, numerous sustainability assessment frameworks (SAFs) exist to guide designers in achieving sustainable performance in the design of structures and communities. SAFs are beneficial in educating users and are useful tools for incorporating sustainability strategies into planning, design, and construction; however, there is currently a substantial gap in the ability of existing SAFs to incorporate hazard resistance and hazard mitigation in the broader context of sustainable design. This paper analyzes the incorporation of hazard resistant design and hazard mitigation strategies within SAFs via a multi-level analysis of eleven SAFs. The SAFs analyzed range in scale of application (i.e. building, site, community). Three levels of analysis are presented: (1) macro-level analysis comparing the number of measures strictly addressing resilience versus sustainability, (2) meso-level analysis of the coverage of types of hazards within SAFs (e.g. flood, fire), and (3) micro-level analysis of SAF measures connected to flood-related hazard resilience. The results demonstrate that hazard resistance and hazard mitigation do not figure prominently in the intent of SAFs and that weaknesses in resilience coverage exist that have the potential to lead to the design of structures and communities that are still highly vulnerable to the impacts of extreme events. - Highlights: • Sustainability assessment frameworks (SAFs) were analyzed for resilience coverage • Hazard resistance and mitigation do not figure prominently in the intent of SAFs • Approximately 75% of SAFs analyzed address three or fewer hazards • Lack of economic measures within SAFs could impact resilience and sustainability • Resilience measures for flood hazards are not consistently included in SAFs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Tradeoffs in forest resilience to satellite-based estimates of water and productivity losses

Climate change is expected to intensify the global hydrological cycle via increased evapotranspiration (ET). Changes in ET have important consequences for water-related ecosystem services as well as for forest productivity. Forests play a critical role in ET: active trees sequester carbon at the expense of losing water, yet if they are not active, water remains in the trees, but productivity stalls. Here, we estimated the capacity of forests to recover (resilience) from extreme water or productivity losses based on modeled ET through remote sensing methods across the conterminous USA. Results show there is a spatial tradeoff in resilience to water or productivity losses. Forests were more resilient to water loss in the drier west, and more resilient to productivity loss in the wetter east. Still, resilience was highly heterogeneous across the continent. Projections under climate change indicate both declines and increases of up to 13% in forest resilience, with broad regional trends but high spatial heterogeneity within regions. This study brings crucial satellite-based insights on how water dynamics, and consequentially productivity and water provision in forests, might be impacted by climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

CyPhyR: a cyber‐physical analysis tool for measuring and enabling resiliency in microgrids

This study presents a tool to study the cyber‐physical resiliency (CyPhyR) of critical energy infrastructure system, in particular the effect of cyber attacks on the microgrid's resiliency. The developed tool enables measuring resiliency using data from cyber and physical systems and suggests control decisions for resilient planning and operation of the microgrid. The microgrid resiliency is formulated based on graph theory based indices and cyber‐power system characteristics. A Common Vulnerability Scoring System based metric called the Cyber Asset Impact Potential is developed and used in the planning phase, and another metric, Cyber Impact Severity is introduced to study the system performance in the operational phase. The information from these two phases is provided to the operator to make informed and proactive decisions to ensure the resilient operation of the microgrid. The performance of the developed tool has been tested using comprehensive real‐time cyber‐power testbed for a Consortium for Electric Reliability Technology Solutions microgrid test system.

Venkataramanan, Venkatesh↗

DOE OSTI2025

Resilient stellarator divertor characteristics in the Helically Symmetric eXperiment

Resilient divertor features connected to open chaotic edge structures in the Helically Symmetric eXperiment are investigated. For the first time, an expanded vessel wall was considered that would give space for implementation of a physical divertor target structure. The analysis was done for four different magnetic configurations with very different chaotic plasma edges. A resilient plasma wall interaction pattern was identified across all configurations. This manifests as qualitatively very similar footprint behavior across the different plasma equilibria. Overall, the resilient field lines of interest with high connection length L C lie within a helical band along the wall for all configurations. This resiliency can be used to identify the best location of a divertor. The details of the magnetic footprint’s resilient helical band is subject to specific field line structures which are linked to the penetration depth of field lines into the plasma and directly influence the heat and particle flux patterns. The differences arising from these details are characterized by introducing a new metric, the minimum radial connection min $(\delta_N)$ of a field line from the last closed flux surface. The relationship, namely the deviation from a scaling law, between min $(\delta_N)$ and L C of the field lines in the plasma edge field line behavior suggests that the field lines are associated with structures such as resonant islands, cantori, and turnstiles. This helps determine the relevant magnetic flux channels based on the radial location of these chaotic edge structures and the divertor target footprint. These details will need to be taken into account for resilient divertor design.

divertor↗

DOE OSTI2024

Diaspora: Resilience-Enabling Services for Real-Time Distributed Workflows

The need for real-time processing to enable automated decision making and experimental steering has driven a shift from high-performance computing workflows on a centralized system to a distributed approach that integrates remote data sources, edge devices, and diverse compute facilities. Under this paradigm, data can be processed close to the source where it is generated, thus reducing latency and bandwidth usage. System resilience is thus a key challenge, requiring distributed workflows to survive component failures and to meet stringent quality-of-service requirements, which results in the need to mitigate anomalies such as congestion and low availability of resources. To address these challenges, we propose Diaspora, a unified resilience framework that is inspired by event-driven communication patterns used in public clouds. Specifically, we propose an event fabric that extends across sites, facilities, and computations to provide timely, reliable, and accurate information about data, application, and resource status. On top of the event fabric, we build resilience-enabling services that combine QoS-aware data streaming, resilient data views, resilient compute and data resources, and anomaly detection and prediction, all of which collectively enhance workflow resilience for these scientific cases.

Rao, Nageswara↗

DOE OSTI2020

Models for Resilience Design Patterns

Resilience plays an important role in supercomputers by providing correct and efficient operation in case of faults, errors, and failures. Resilience design patterns offer blueprints for effectively applying resilience technologies. Prior work focused on developing initial efficiency and performance models for resilience design patterns. This paper extends it by (1) describing performance, reliability, and availability models for all structural resilience design patterns, (2) providing more detailed models that include flowcharts and state diagrams, and (3) introducing the Resilience Design Pattern Modeling (RDPM) tool that calculates and plots the performance, reliability, and availability metrics of individual patterns and pattern combinations.

Kumar, Mohit↗

DOE OSTI2020

Resilient Microgrid Scheduling Considering Multi-Level Load Priorities

In this paper, we propose a novel resilient microgrid scheduling model considering the multi-level load priorities. The resiliency of the microgrid is guaranteed by quickly adjusting the output of committed local resources and shedding the loads with low priorities when the power supply from the main grid is interrupted. Considering the uncertainty of renewable energy resources and loads as well as exchanged power at PCC, the probability of successful islanding (PSI) is used to quantify the resiliency of electricity supply for various loads with different priorities. Then, the multi-level priorities are enforced through chance constrains. Results of numerical simulation validate the proposed resilient scheduling model. In addition, the impacts of resiliency requirement of loads with high priority on the resiliency of loads with low priority are analyzed as well.

Liu, Guodong↗

DOE OSTI2024

HAPPA: A Modular Platform for HPC Application Resilience Analysis with LLMs Embedded

High-performance computing (HPC) systems are increasingly vulnerable to soft errors, which pose significant challenges in maintaining computational accuracy and reliability. Predicting the resilience of HPC applications to these errors is crucial for robust code protection and detailed resilience analysis. In this study, we present HAppA, a modular platform designed for HPC Application Resilience Analysis. Embedding Large Language Models (LLMs), HAppA addresses understanding the context information of long code sequences typical in HPC applications. HAppA implements a novel code representation module that chunks the code into fixed-size segments and aggregates the embeddings of these segments. Three aggregation methods have been explored: MeanPooling, MaxPooling, and LSTM-based techniques. We built a DAtaset for REsilience analysis using Fault Injection (FI), named DARE. Using our DARE dataset, HAppA is trained for regression prediction tasks. Our evaluation results demonstrate the predictive accuracy of HAppA compared to other models, particularly noting that the LSTM-based aggregation method -- HAppA-LSTM -- achieves a mean squared error (MSE) of 0.078 for SDC prediction, surpassing the existing state-of-the-art PARIS model, which recorded an MSE of 0.1172. Additionally, HAppA with the KeyBERT model extracts a list of keywords representing the source code. A comprehensive importance analysis of these keywords further elucidates the code patterns contributing to the error rate. These findings highlight the effectiveness of HAppA in analyzing the resilience of HPC applications and establish a new benchmark for predictive accuracy in resilience.

Jiang, Hailong [Kent State University]↗

DOE OSTI2025

Techno-Economic Analysis of Data-Driven and Transactive Approaches for Resilience Enhancement

As extreme weather events lead to more frequent power outages, understanding and enhancing grid resilience is critical to mitigating economic losses and non-energy impacts from service disruptions. Here, this study introduces a novel techno-economic analysis framework for evaluating resilience enhancement mechanisms. The framework combines grid response modeling with a co-simulation approach and valuation methodology to provide a comprehensive assessment. We apply this framework to a realistic case study of the Texas grid during Winter Storm Uri in February 2021. Two advanced resilience strategies are analyzed: a data-driven rolling outage mechanism and a transactive energy (TE) based allocation scheme. The rolling outage scheme selectively serves customers based on real-time curtailment needs, while the TE scheme allows customers to trade energy allocations according to their preferences. Our findings show that both the rolling outage and TE schemes significantly outperform conventional methods (i.e. controlled outages) by reducing the amount of energy not supplied to customers by 41% and 64%, respectively. These approaches also enhance flexibility and customer satisfaction, while improving energy utilization for greater resilience. Additionally, they maintain thermal comfort about 3.5 times better and substantially lower customer risk exposure. A key contribution of this study is addressing both utility and customer perspectives while considering both energy and non-energy impacts. The techno-economic analysis indicates that implementing these resilience enhancement strategies would incur an additional 1.1Bto1.6B in utility costs but has the potential to avoid 17.3Bto18B of customer losses as compared to existing solutions, thereby underscoring the value of investing in advanced resilience, as it provides significant societal benefits to customers.

42 ENGINEERING↗

DOE OSTI2022

Linking soil phosphorus with forest litterfall resistance and resilience to cyclone disturbance: A pantropical meta-analysis

While tropical cyclone regimes are shifting with climate change, the mechanisms underpinning the resistance (ability to withstand disturbance-induced change) and resilience (capacity to return to pre-disturbance reference) of tropical forest litterfall to cyclones remain largely unexplored pantropically. Single-site studies in Australia and Hawaii suggest that litterfall on low-phosphorus (P) soils is more resistant and less resilient to cyclones. Here, we conducted a meta-analysis to investigate the pantropical importance of total soil P in mediating forest litterfall resistance and resilience to 22 tropical cyclones. We evaluated cyclone-induced and post-cyclone litterfall mass (g/m 2 /day), and P and nitrogen (N) fluxes (mg/m 2 /day) and concentrations (mg/g), all indicators of ecosystem function and essential for nutrient cycling. Across 73 case studies in Australia, Guadeloupe, Hawaii, Mexico, Puerto Rico, and Taiwan, total litterfall mass flux increased from ~2.5 ± 0.3 to 22.5 ± 3 g/m 2 /day due to cyclones, with large variation among studies. Litterfall P and N fluxes post-cyclone represented ~5% and 10% of the average annual fluxes, respectively. Post-cyclone leaf litterfall N and P concentrations were 21.6 ± 1.2% and 58.6 ± 2.3% higher than pre-cyclone means. Mixed-effects models determined that soil P negatively moderated the pantropical litterfall resistance to cyclones, with a 100 mg P/kg increase in soil P corresponding to a 32% to 38% decrease in resistance. Based on 33% of the resistance case studies, total litterfall mass flux reached pre-disturbance levels within one-year post-disturbance. A GAMM indicated that soil P, gale wind duration and time post-cyclone jointly moderate the short-term resilience of total litterfall, with the nature of the relationship between resilience and soil P contingent on time and wind duration. Across pantropical forests observed to date, our results indicate that litterfall resistance and resilience in the face of intensifying cyclones will be partially determined by total soil P.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

A Pattern Language for High-Performance Computing Resilience

High-performance computing systems (HPC) provide powerful capabilities for modeling, simulation, and data analytics for a broad class of computational problems. They enable extreme performance of the order of quadrillion floating-point arithmetic calculations per second by aggregating the power of millions of compute, memory, networking and storage components. With the rapidly growing scale and complexity of HPC systems for achieving even greater performance, ensuring their reliable operation in the face of system degradations and failures is a critical challenge. System fault events often lead the scientific applications to produce incorrect results, or may even cause their untimely termination. The sheer number of components in modern extreme-scale HPC systems and the complex interactions and dependencies among the hardware and software components, the applications, and the physical environment makes the design of practical solutions that support fault resilience a complex undertaking. To manage this complexity, we developed a methodology for designing HPC resilience solutions using design patterns. We codified the well-known techniques for handling faults, errors and failures that have been devised, applied and improved upon over the past three decades in the form of design patterns. In this paper, we present a pattern language to enable a structured approach to the development of HPC resilience solutions. The pattern language reveals the relations among the resilience patterns and provides the means to explore alternative techniques for handling a specific fault model that may have different efficiency and complexity characteristics. Using the pattern language enables the design and implementation of comprehensive resilience solutions as a set of interconnected resilience patterns that can be instantiated across layers of the system stack.

Hukerikar, Saurabh↗

DOE OSTI2018

Analysis of Microgrid Locations Benefitting Community Resilience for Puerto Rico

An analysis of microgrids to increase resilience was conducted for the island of Puerto Rico. Critical infrastructure throughout the island was mapped to the key services provided by those sectors to help inform primary and secondary service sources during a major disruption to the electrical grid. Additionally, a resilience metric of burden was developed to quantify community resilience, and a related baseline resilience figure was calculated for the area. To improve resilience, Sandia performed an analysis of where clusters of critical infrastructure are located and used these suggested resilience node locations to create a portfolio of 159 microgrid options throughout Puerto Rico. The team then calculated the impact of these microgrids on the region's ability to provide critical services during an outage, and compared this impact to high-level estimates of cost for each microgrid to generate a set of efficient microgrid portfolios costing in the range of $\$218$-$\$917$M. This analysis is a refinement of the analysis delivered on June 01, 2018.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Solar and Energy Storage for Resiliency

Facilitated by a grant from the U.S. Department of Energy, the San Francisco Department of the Environment (SF Environment) is working to overcome regulatory, financial and technical barriers and create a roadmap to build resilience through the implementation of solar with energy storage. One key element of resilience is ensuring the continued operation of shelters and critical emergency management facilities in the immediate aftermath of an earthquake, flood, or other disaster, such as a nearby wildfire. To mitigate interruptions to emergency power at these facilities, the City and County of San Francisco (the “City”) has established “on call” contracts with national diesel generator suppliers. However, relying solely on these suppliers poses significant risks to the City, because the supply of diesel generators in San Francisco may be limited when they are most needed, especially during hurricane season when coastal states face an increased risk of power outages. Furthermore, although diesel generators can provide a few days of power when the electric grid is down, they rely on fuel to do so, and fuel supplies can be interrupted by disasters. To help the City address these challenges, a Resilient Solar and Storage Roadmap study was completed in 2017 that investigated the use of microgrids and standalone solar electric generation with battery storage at emergency shelters. The study identified 67 facilities across the City where solar and battery storage systems could be installed. Out of the 67 facilities, 42 are classified as community shelters, where people can live temporarily and receive medical attention for nonserious injuries, and 25 are libraries where people can gather and have free access to communication/information channels (internet access for communication, news, etc.). At present, none of the emergency shelter facilities have back-up power or generators on site. The Solar and Energy Storage for Resilience project (the “Project) is intended to provide electricity to 67 emergency shelters within the City in the wake of a disaster, by implementing stand-alone solar power generation with battery storage. This report aims to provide an assessment of the economic value and resilience benefits derived from the implementation of a solar and energy storage system at emergency shelters. This assessment is based on quantifiable metrics and grounded in a proven economic benefit-cost analysis (BCA) methodology, which help decision makers assess whether the benefits of a project or policy exceed its total costs from a societal perspective. This is a first-of -its-kind study and it is not meant to be comprehensive. The Project Team hopes that other organizations/municipalities will use this report as a reference and refine it for use in future economic assessments on resiliency at emergency shelters. While the report focuses on a study for the City and County of San Francisco, the methods are applicable to any city or town. The analysis is intended to help the City better prepare for the next large-scale grid outage by weighing the benefits and costs of implementing a solar energy system.

14 SOLAR ENERGY↗

DOE OSTI2018

Analysis of Microgrid Locations Benefitting Community Resilience for Puerto Rico

An analysis of microgrids to increase resilience was conducted for the island of Puerto Rico. Critical infrastructure throughout the island was mapped to the key services provided by those sectors to help inform primary and secondary service sources during a major disruption to the electrical grid. Additionally, a resilience metric of burden was developed to quantify community resilience, and a related baseline resilience figure was calculated for the area. To improve resilience, Sandia performed an analysis of where clusters of critical infrastructure are located and used these suggested resilience node locations to create a portfolio of 159 microgrid options throughout Puerto Rico. The team then calculated the impact of these microgrids on the region's ability to provide critical services during an outage, and compared this impact to high-level estimates of cost for each microgrid to generate a set of efficient microgrid portfolios costing in the range of 218-917M dollars. This analysis is a refinement of the analysis delivered on June 01, 2018.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Workshop on the Nexus of Resilience and Energy Efficiency in Buildings: Proceedings Report

There is an array of building technologies whose operation–either passively or actively–holds the potential to improve resilience for building occupants and owners, utilities, communities, and other financial interests. Recent decades have witnessed enhanced resilience to major disruptions, as well as significant improvements in the energy efficiency of building technologies. However, these dual goals have often been pursued independently of each other. Similar levels of energy efficiency can be realized by a range of different technologies. For example, buildings can be kept cool in summer through passive ventilation, more efficient heating, ventilation, and air conditioning (HVAC), higher quality walls and windows, advanced control systems, and intelligent analytics enabled by IoT technology. However, each of these technologies realizes energy efficiency through a different mechanism, and those mechanisms may contribute to resilience in non-uniform ways. One purpose of this workshop was the identification of specific energy efficiency and load flexibility characteristics, followed by an assessment of how those characteristics map onto the resilience space. In June 2019, Oak Ridge National Laboratory hosted a two-day workshop to explore how and where the two areas overlap, complement, or interfere with each other. A diverse group of experts assembled to discuss how to mutually address goals for improving the efficiency and resilience of our nation’s buildings. While this workshop only considered energy efficiency and load flexibility technologies that were realized through behind-the-meter technologies, all forms of resilience were considered. That is, the impact of these technologies on building occupants, building owners, business operators, utilities, communities, and all other relevant stakeholders were within scope.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Mixed Integer Nonlinear Programming Approaches to Enhance Resiliency and Response Strategies in Critical Infrastructure

Motivation. Critical infrastructures are large, complex engineered systems that must be operated robustly under abnormal conditions resulting from natural hazards or intentional acts. For example, electric power systems must be robust to line faults, water utilities must rapidly mitigate contamination incidents, and computing networks must adapt to adversarial intrusions to protect critical information. Problem. It is difficult for decision-makers within resiliency analysis in critical infrastructure to optimize designs and develop effective response strategies that can account for uncertainties. Facing incomplete information and the sheer scope that a natural hazard or attack vector may incorporate, response can be ineffective without reliable, scalable decision support tools. These problems are intrinsically nonlinear and involve discrete decisions, and unfortunately, existing off-the-shelf mathematical programming methods cannot support optimization-based decision-making of these nonlinear at scale. Method/Approach and Results. This project emphasized development of fundamental optimization strategies that supported real- time mitigation and response for critical infrastructures. In particular, the project developed multi- tree approaches based on piecewise outer-approximations for solution of mixed-integer nonlinear programming (MINLP) problems. These techniques alternate between an MILP or MISOCP relaxation to obtain a lower bound and candidate discrete solutions and an NLP subproblem to obtain upper bounds. Using tailored relaxations based on problem structure, these methods were used to solve several key applications in resilience and response of critical infrastructure. This work resulted in two open-source, copyrighted software packages: CORAMIN (https://github.com/Coramin/Coramin) -- an object-oriented mathematical programming framework that supports tailored multi-tree algorithms for solution of large- scale mixed-integer nonlinear programming; and EGRET (Electrical Grid Research and Engineering Toolkit) (https://github.com/grid- parity-exchange/Egret) -- a declarative mathematical programming framework built upon CORAMIN and Pyomo for formulation and solution of resilience and operations problems in power grid systems. Furthermore, these tools resulted in several important published results, including the following: The first known global optimization approach that could solve the unit-commitment problem with nonlinear power flow constraints on medium-sized test problems; Improved parallel optimization-based bounds tightening and strengthening of relaxations of AC power flow constraints; and, Optimization-based approaches for improved grid resilience and use of demand response to improve grid resilience with reduction in capital requirements. Result Implications. This project developed first-of-a-kind algorithms for decision-making in critical infrastructure resilience operations and planning, as well as a next-generation toolkit for MINLP researchers. These approaches leveraged high-performance computing architectures to solve some of the largest, most challenging nonlinear discrete optimization problems to global optimality, and these successes were captured in open-source software to enable optimization-based decision-making, and efficient solution of MINLP formulations for electric power transmission grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Electric Grid Resilience and Reliability for Grid Architecture

Grid modernization activities cite resilience (sometimes called resiliency) as a key electric power grid characteristic to be improved or maximized, and so it is crucial for the development of resilient grid architectures that the concept of grid resilience be clear and quantifiable. However, attempts to define and quantify a concept of resilience for electric power grids have mostly relied upon ad hoc definitions that do not have much underlying rigor and are often closely tied to reliability, sometimes only differing in terms of scale and frequency of events. While grid reliability would seem to have strong definition given the IEEE 1366 standard, grid resilience is a term that is less clear.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Integration of equitable resilience metrics into climate-informed electric utility planning processes: phase one

Working together, Sandia National Laboratories, Southern California Edison (SCE) - an Investor-Owned Utility (IOU) - and the California Public Utilities Commission (CPUC) are studying how electric utilities can use equity and resilience metrics to help inform the prioritization and sequencing of resilience-driven infrastructure investments. To this end, this project evaluated “Social Burden,” an equitable resilience metric which measures the potential impact of disruptions in access to non-electric critical services on people and estimates community resilience to these disruptions. The Social Burden was expanded to incorporate SCE’s existing equity metric and applied to evaluate the potential impacts from a range of climate-informed hypothetical outage scenarios developed under SCE’s 2022 Climate Adaptation Vulnerability Assessment. One baseline (“blue-sky”) state and eight different outage scenarios were evaluated to measure the potential impacts of the outages on non-electric infrastructure, critical services, and people. Key findings include: 1) the Social Burden framework is flexible enough to adapt to and build upon existing utility equity and/or resilience metrics, 2) Social Burden results highlight the high degree of non-electric service redundancy within the SCE service area with most (6/8) hypothetical outage scenarios predicted to increase people’s Social Burden by less than 10%; however, 3) access to critical services and people’s ability to obtain them is unequal and spatially clustered, meaning that there are some hypothetical outage scenarios (2/8) that will exert a higher toll on communities directly experiencing the outage as well as some nearby communities with pre-existing vulnerabilities. The report concludes with recommendations for potential use cases of the expanded Social Burden metric and identifies priority follow-on work. Potential use cases may include incorporating equity into IOU’s prioritization of climate resilience investments. Additionally, Social Burden analysis may provide additional data and insights to augment grid planning, potentially by identifying additional needs and/or prioritizing previously identified needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗