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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-T-316: The Design of a Risk Index Method for 3D Patient Specific QA

Purpose: To suggest a new guidance for the evaluation of 3D patient specific QA, a structure-specific risk-index (RI) method was designed and implemented. Methods: A new algorithm was designed to assign the score of Pass, Fail or Pass with Risk to all 3D voxels in each structure by improving a conventional Gamma Index (GI) algorithm, which implied the degree of the risk of under-dose to the treatment target or over-dose to the organ at risks (OAR). Structure-specific distance to agreement (DTOA), dose difference and minimum checkable dose were applied to the GI algorithm, and additional parameters such as dose gradient factor and dose limit of structures were used to the RI method. Maximum passing rate (PR) and minimum PR were designed and calculated for each structure with the RI method. 3D doses were acquired from a spine SBRT plan by simulating the shift of beam iso-center, and tested to show the feasibility of the suggested method. Results: When the iso-center was shifted by 1 mm, 2 mm, and 3 mm, the PR of conventional GI method between shifted and non-shifted 3D doses were 99.9%, 97.4%, and 89.7% for PTV, 99.8%, 84.8%, and 63.2% for spinal cord, and 100%, 99.5%, 91.7% for right lung. The minimum PRs from the RI method were 98.9%, 96.9%, and 89.5% for PTV, and 96.1%, 79.3%, 57.5% for spinal cord, and 92.5%, 92.0%, 84.4% for right lung, respectively. The maximum PRs from the RI method were equal or less than the PRs from the conventional GI evaluation. Conclusion: Designed 3D RI method showed more strict acceptance level than the conventional GI method, especially for OARs. The RI method is expected to give the degrees of risks in the delivered doses, as well as the degrees of agreements between calculated 3D doses and measured (or simulated) 3D doses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Sci—Sat AM: Stereo — 08: Stereotactic Ablative Radiotherapy (SABR) for low, intermediate and high risk prostate cancer using Volumetric Modulated Arc Therapy (VMAT) with a 10x Flattening Filter Free (FFF) beam

Purpose: To determine the feasibility of using Volumetric Modulated Arc Therapy (VMAT) with a 10x Flattening Filter Free (FFF) beam for Stereotactic Ablative Radiotherapy (SABR) for low, intermediate and high risk prostate cancer. Methods and Materials: Ten anonymized patient CT data sets were used in this planning study. For each patient CT data set, three sets of contours were generated: 1) low risk, 2) intermediate risk, and 3) high risk scenarios. For each scenario, a single-arc and a double-arc VMAT treatment plans were created. Plans were generated with the Varian Eclipse™ treatment planning system for a Varian TrueBeam™ linac equipped with Millenium 120 MLC. Plans were created using a 10x-FFF beam with a maximum dose rate of 2400 MU/min. Dose prescription was 36.25Gy/5 fractions with the planning objective of covering 99% of the Planning Target Volume with the 95% of the prescription dose. Normal tissue constraints were based on provincial prostate SABR planning guidelines, derived from national and international prostate SABR protocols. Plans were evaluated and compared in terms of: 1) dosimetric plan quality, and 2) treatment delivery efficiency. Results: Both single-arc and double-arc VMAT plans were able to meet the planning goals for low, intermediate and high risk scenarios. No significant dosimetric differences were observed between the plans. However, the treatment time was significantly lower for a single-arc VMAT plans. Conclusions: Prostate SABR treatments are feasible with 10x-FFF VMAT technique. A single-arc VMAT offers equivalent dosimetric plan quality and a superior treatment delivery efficiency, compared to a double-arc VMAT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-201-12: Designing a Risk-Based Quality Assurance Program for a Newly Implemented Y-90 Microspheres Procedure

Purpose: To create a quality assurance program based upon a risk-based assessment of a newly implemented SirSpheres Y-90 procedure. Methods: A process map was created for a newly implemented SirSpheres procedure at a community hospital. The process map documented each step of this collaborative procedure, as well as the roles and responsibilities of each member. From the process map, different potential failure modes were determined as well as any current controls in place. From this list, a full failure mode and effects analysis (FMEA) was performed by grading each failure mode’s likelihood of occurrence, likelihood of detection, and potential severity. These numbers were then multiplied to compute the risk priority number (RPN) for each potential failure mode. Failure modes were then ranked based on their RPN. Additional controls were then added, with failure modes corresponding to the highest RPNs taking priority. Results: A process map was created that succinctly outlined each step in the SirSpheres procedure in its current implementation. From this, 72 potential failure modes were identified and ranked according to their associated RPN. Quality assurance controls and safety barriers were then added for failure modes associated with the highest risk being addressed first. Conclusion: A quality assurance program was created from a risk-based assessment of the SirSpheres process. Process mapping and FMEA were effective in identifying potential high-risk failure modes for this new procedure, which were prioritized for new quality assurance controls. TG 100 recommends the fault tree analysis methodology to design a comprehensive and effective QC/QM program, yet we found that by simply introducing additional safety barriers to address high RPN failure modes makes the whole process simpler and safer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Evaluating the mineral commodity supply risk of the U.S. manufacturing sector

Trade tensions, resource nationalism, and various other factors are increasing concerns regarding the supply reliability of nonfuel mineral commodities. This is especially the case for commodities required for new and emerging technologies ranging from electric vehicles to wind turbines. In this analysis, we use a conventional risk-modeling framework to develop and apply a new methodology for assessing the supply risk to the U.S. manufacturing sector. Specifically, supply risk is defined as the confluence of three factors: the likelihood of a foreign supply disruption, the dependency of U.S. manufacturers on foreign supplies, and the ability of U.S. manufacturers to withstand a supply disruption. The methodology is applied to 52 commodities for the decade spanning 2007–2016. The results indicate that a subset of 23 commodities, including cobalt, niobium, rare earth elements, and tungsten, pose the greatest supply risk. This supply risk is dynamic, shifting with changes in global market conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Differential patterns of reproductive and lifestyle risk factors for breast cancer according to birth cohorts among women in China, Japan and Korea

Background: The birth cohort effect has been suggested to influence the rate of breast cancer incidence and the trends of associated reproductive and lifestyle factors. We conducted a cohort study to determine whether a differential pattern of associations exists between certain factors and breast cancer risk based on birth cohorts. Methods: This was a cohort study using pooled data from 12 cohort studies. We analysed associations between reproductive (menarche age, menopause age, parity and age at first delivery) and lifestyle (smoking and alcohol consumption) factors and breast cancer risk. We obtained hazard ratios (HRs) with 95% confidence intervals (CIs) using the Cox proportional hazard regression analysis on the 1920s, 1930s, 1940s and 1950s birth cohorts. Results: Parity was found to lower the risk of breast cancer in the older but not in the younger birth cohort, whereas lifestyle factors showed associations with breast cancer risk only among the participants born in the 1950s. In the younger birth cohort group, the effect size was lower for parous women compared to the other cohort groups (HR [95% CI] 0.86 [0.66–1.13] compared to 0.60 [0.49–0.73], 0.46 [0.38–0.56] and 0.62 [0.51–0.77]). Meanwhile, a higher effect size was found for smoking (1.45 [1.14–1.84] compared to 1.25 [0.99–1.58], 1.06 [0.85–1.32] and 0.86 [0.69–1.08]) and alcohol consumption (1.22 [1.01–1.48] compared to 1.10 [0.90–1.33], 1.15 [0.96–1.38], and 1.07 [0.91–1.26]). Conclusion: We observed different associations of parity, smoking and alcohol consumption with breast cancer risk across various birth cohorts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Epi-Regularization of Risk Measures

Uncertainty pervades virtually every branch of science and engineering, and in many disciplines, the underlying phenomena can be modeled by partial differential equations (PDEs) with uncertain or random inputs. This work is motivated by risk-averse stochastic programming problems constrained by PDEs. These problems are posed in infinite dimensions, which leads to a significant increase in the scale of the (discretized) problem. In order to handle the inherent nonsmoothness of, for example, coherent risk measures and to exploit existing solution techniques for smooth, PDE-constrained optimization problems, we propose a variational smoothing technique called epigraphical (epi-)regularization. Here, we investigate the effects of epi-regularization on the axioms of coherency and prove differentiability of the smoothed risk measures. In addition, we demonstrate variational convergence of the epi-regularized risk measures and prove the consistency of minimizers and first-order stationary points for the approximate risk-averse optimization problem. We conclude with numerical experiments confirming our theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Sensemaking, stakeholder discord, and long-term risk communication at a US Superfund site

Abstract Introduction: Risk communication can help reduce exposures to environmental contaminants, mitigate negative health outcomes, and inform community-based decisions about hazardous waste sites. While communication best practices have long guided such efforts, little research has examined unintended consequences arising from such guidelines. As rhetoric informs stakeholder sensemaking, the language used in and reinforced by these guidelines can challenge relationships and exacerbate stakeholder tensions. Objectives: This study evaluates risk communication at a U.S. Superfund site to identify unintended consequences arising from current risk communication practices. Methods: This qualitative case study crystallizes data spanning 6 years from three sources: 1) local newspaper coverage of site-related topics; 2) focus-group transcripts from a multi-year project designed to support future visioning of site use; and 3) published blog entries authored by a local environmental activist. Constant comparative analysis provides the study’s analytic foundation, with qualitative data analysis software QSR NVivo 8 supporting a three-step process: 1) provisional coding to identify broad topic categories within datasets, 2) coding occurrences of sensemaking constructs and emergent intra-dataset patterns, and 3) grouping related codes across datasets to examine the relationships among them. Results: Existing risk communication practices at this Superfund site contribute to a dichotomous conceptualization of multiple and diverse stakeholders as members of one of only two categories: the government or the public. This conceptualization minimizes perceptions of capacity, encourages public commitment to stances aligned with a preferred group, and contributes to negative expectations that can become self-fulfilling prophecies. Conclusion: Findings indicate a need to re-examine and adapt risk communication guidelines to encourage more pluralistic understanding of the stakeholder landscape.

Environmental Sciences & Ecology↗
DOE OSTI2025

Deep Learning–Assisted Multiobjective Optimization of Geological CO 2 Storage Performance under Geomechanical Risks

In geological CO 2 storage, designing the optimal well control strategy for CO 2 injection to maximize CO 2 storage while minimizing the associated geomechanical risks is not trivial. This challenge arises due to pressure buildup, CO 2 plume migration, the highly nonlinear nature of geomechanical responses to rock-fluid interaction, and the high computational cost associated with coupled flow and geomechanics simulations. In this paper, we introduce a novel optimization framework to address these challenges. The optimization problem is formulated as follows: maximize total CO 2 storage while minimizing geomechanical risks by adjusting the injection schedules within bounded constraints. The geomechanical risks are primarily driven by injection-induced pressure build-up, which is characterized by ground displacement and the induced microseismicity. We used the Fourier neural operator (FNO)-based deep learning model to construct surrogate models, replacing the time-consuming coupled flow and geomechanics simulations for evaluating the aforementioned objective functions. The developed surrogate models have been incorporated into a multiobjective optimization framework through a genetic algorithm to reduce the computational burden. The proposed optimization framework reduces the computational cost from approximately 2,400 hours, when using objective function evaluations based on physics-based simulations, to around 20 minutes. A set of Pareto-optimal solutions of the proposed workflow yields nontrivial optimal decisions, reducing the microseismicity potential and the vertical displacement. This Pareto front highlights the optimal trade-offs between CO 2 storage amount, safety, and ground displacement, emphasizing the need for careful optimization and management of injection strategies to achieve a balanced outcome. The novelty of this work is twofold. First, we demonstrate the importance of incorporating the minimization of the geomechanical risks as objective functions into the CO 2 storage optimization workflow to mitigate the potential risk of induced microseismicity and ground displacement. Second, we leverage the FNO-based surrogate models to optimize a real-field CO 2 storage operation.

42 ENGINEERING↗
DOE OSTI2013

Deployment and Overview of RAVEN Capabilities for a Probabilistic Risk Assessment Demo for a PWR Station Blackout

Starting in 2012, Idaho National Laboratory (INL) has been engaged to provide tools and methodologies to support a new approach to safety assessment and management of safety related issues for Nuclear Power Plants (NPPs). This activity is placed under the Risk Informed Safety Margin Characterization (RISMC) [2] umbrella that is one of the technical paths of the Department Of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. RISMC takes a broader approach to risk evaluation by generating more comprehensive information. This information is used to gain a more accurate estimation of risk margins and to highlight feasible improvements that seek the optimal point between risk mitigation and economical viability of the nuclear energy option. This is, of course, done without taking any judgmental approach with respect to risk, which is a regulatory body task, and the economical viability, which is up to the single states and the open electricity market. RISMC is therefore composed of methodologies and tools. The augmented information that RISMC seeks to generate, as enabling decision tool, is not holistic with respect all possible metrics and operational aspects of a power plant; it is rather channeled toward the improvement of safety and the associated economical impact. While these are indeed two very broad metrics, they still allow a focus within the development of the underlying tools that, in a resource constrained environment (DOE founding, computational, mathematical) maximize the benefit of the program to the nuclear industry.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2013

Use of limited data to construct Bayesian networks for probabilistic risk assessment.

Probabilistic Risk Assessment (PRA) is a fundamental part of safety/quality assurance for nuclear power and nuclear weapons. Traditional PRA very effectively models complex hardware system risks using binary probabilistic models. However, traditional PRA models are not flexible enough to accommodate non-binary soft-causal factors, such as digital instrumentation&control, passive components, aging, common cause failure, and human errors. Bayesian Networks offer the opportunity to incorporate these risks into the PRA framework. This report describes the results of an early career LDRD project titled %E2%80%9CUse of Limited Data to Construct Bayesian Networks for Probabilistic Risk Assessment%E2%80%9D. The goal of the work was to establish the capability to develop Bayesian Networks from sparse data, and to demonstrate this capability by producing a data-informed Bayesian Network for use in Human Reliability Analysis (HRA) as part of nuclear power plant Probabilistic Risk Assessment (PRA). This report summarizes the research goal and major products of the research.

Groth, Katrina M.↗
DOE OSTI2015

Comparative Study of Barotrauma Risk during Fish Passage through Kaplan Turbines

Rapid pressure changes in hydroelectric turbine flows can cause barotrauma that can be hazardous to the passage of fish, in particular migratory juvenile salmonids. Although numerous laboratory tests have evaluated the effect of rapid decompression in fish species of relevance, numerical modeling studies offer the advantage of predicting, for new turbine designs, the potential risks of mortality and injury from rapid pressure change during turbine passage. However, rapid pressure change is only one of several hydraulic risks encountered by fish during turbine passage in addition to blade strike, shear, and turbulence. To better understand the role of rapid pressure changes, the present work focuses on the application of a computational fluid dynamics based method for evaluating the risk of pressure-related mortality to fish passing through an early 1960s era original hydroelectric Kaplan turbine at Wanapum Dam (Columbia River, Washington), and a modern advanced Kaplan turbine installed in 2005. The results show that the modeling approach acceptably reproduced the nadir pressure distributions compared to field data previously collected at the site using an autonomous sensor. Our findings show that the new advanced-design unit performs better, in terms of reduced barotrauma risk to fish from exposure to low pressures, than the original turbine unit. The outcomes allow for comparative analyses of turbine designs and operations prior to installation, an advantage that can potentially be integrated in the process of designing new turbine units to achieve superior environmental performance. Overall, the results show that modern turbine designs can achieve the multiple objectives of increasing power generation, lowering cavitation potential, and reducing barotrauma risks to passing fish.

13 HYDRO ENERGY↗
DOE OSTI2016

Effect of Using Different Vehicle Weight Groups on the Estimated Relationship Between Mass Reduction and U.S. Societal Fatality Risk per Vehicle Miles of Travel

This report recalculates the estimated relationship between vehicle mass and societal fatality risk, using alternative groupings by vehicle weight, to test whether the trend of decreasing fatality risk from mass reduction as case vehicle mass increases, holds over smaller increments of the range in case vehicle masses. The NHTSA baseline regression model estimates the relationship using for two weight groups for cars and light trucks; we re-estimated the mass reduction coefficients using four, six, and eight bins of vehicle mass. The estimated effect of mass reduction on societal fatality risk was not consistent over the range in vehicle masses in these weight bins. These results suggest that the relationship indicated by the NHTSA baseline model is a result of other, unmeasured attributes of the mix of vehicles in the lighter vs. heavier weight bins, and not necessarily the result of a correlation between mass reduction and societal fatality risk. An analysis of the average vehicle, driver, and crash characteristics across the various weight groupings did not reveal any strong trends that might explain the lack of a consistent trend of decreasing fatality risk from mass reduction in heavier vehicles.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Quantitative Risk Analysis

The US energy sector is vulnerable to multiple hazards including both natural disasters and malicious attacks from an intelligent adversary. The question that utility owners, operators and regulators face is how to prioritize their investments to mitigate the risks from a hazard that can have the most impact on the asset of interest. In order to be able to understand their risk landscape and develop a prioritized mitigation strategy, they must quantify risk in a consistent way across all hazards their asset is facing. Without being able to quantitatively measure risk, it is not possible to defensibly prioritize security investments or evaluate trade-offs between security and functionality. Development of a methodology that will consistently measure and quantify risk across different hazards is needed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Additive Manufacturing and Nuclear Security: Calibrating Rewards and Risks

In a security environment marked by a high degree of technological dynamism, additive manufacturing (AM) stands out for its special significance. The AM field has emerged from infancy, with many new and potential applications in the commercial and military sectors. Its potential impact on nuclear security is a matter of rising debate, with some emphasizing the disruptive consequences of AM competition for international stability and others emphasizing the disruptive benefits for the United States. This essay addresses both aspects and draws on a technical analysis to inform the further development of U.S. policy. From a nuclear-security perspective, additive manufacturing offers both rewards and risks for the United States and its allies. The rewards are primarily (1) reduced scale of effort and cost in maintaining weapons-production infrastructure and (2) greatly increased responsiveness and agility in production infrastructure. Both these benefits are long-standing U.S. policy goals. The risks derive from the potential impact of AM on foreign nuclear weapons programs and are of three kinds. Those impacts will likely be a function of the degree of technical sophistication of the foreign actor. Non-state actors and entry-level proliferants pose modest AM risks relative to more advanced states, including both existing nuclear-weapon- states and those developed countries with a high degree of nuclear latency. A critical factor in predicting the impact of AM is current uncertainty as to the utility of AM techniques in the fabrication of special nuclear materials. To meet the emerging challenges of AM, U.S. policy makers face a number of decisions regarding which benefits to seek, how much risk to accept, and how to reduce that risk. The basic strategic approach of the United States to the AM problem is sound, but some fine-tuning is necessary and appropriate at this time. The good news is that we have time to act; the bad news is that the time to act decisively may be shorter than we would wish.

42 ENGINEERING↗
DOE OSTI2019

In Recognition of Sandia's SCRM Program, Delivering Over 500 Subcontractor Risk Assessments in 2018

The globalization of modern supply chains has resulted in many new risks to Sandia's NW programs and mission. The potential impact of counterfeit products, tampering, theft, malicious software, poor manufacturing and/or development practices, and the influence of foreign governments has become more obvious as new threats and compromises continuously emerge. The Supply Chain Risk Management (SCRM) team was formed specifically to understand and address these risks. We were able to coalesce around these principles to develop and optimize an effective risk assessment process for critical suppliers, called Subcontractor Risk Assessments (SRAs). These elevated screening techniques are planned and delivered in a cost-effective way for Sandia's programs (no increase to purchasing burden rates) and also demonstrate due diligence to DOE/NNSA as a component of Sandia's overall SCRM strategy. SRAs are communicated in a concise 1-page format complete with recommendations as well as links to reference materials for those who require additional details about the SRA process and results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Risk-Informed Analysis for an Enhanced Resilient PWR with ATF, FLEX, and Passive Cooling

This report documents the activities performed by Idaho National Laboratory (INL) during the fiscal year (FY) 2019 for the DOE Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of Accident Tolerant Fuel (ATF), optimal use of Diverse and Flexible Coping Strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. The FY 2019 efforts documented in this report is an extension of those conducted in FY 2018. The same analysis process, risk analysis approaches, and analysis tools as in FY 2018 are used for near-term ATF cladding [i.e., Iron-Chromium-Aluminum (FeCrAl) cladding and Chromium (Cr) coated cladding] designs under the postulated loss of feedwater (LOFW) and steam generator tube rupture (SGTR) accident scenarios. In addition, FLEX analysis was presented for an overview of FLEX equipment and strategies implemented in nuclear industry after Fukushima accident. A FLEX model was developed and incorporated into the generic SAPHIRE model to assess the risk impact from FLEX. FLEX HRA analysis was performed which suggested an approach to HRA with FLEX strategies. Passive cooling system analysis includes an overview of the DNC system, the RELAP5-3D simulations of the DNC system in selected SBO scenarios, and the evaluation of the DNC system risk impact using the generic PRA model.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

200-IA-1 Operable Unit Human Health Risk and Kd Screen

The purpose of this environmental calculation file (ECF) is to provide the following: Document the data processing and data reduction steps taken to prepare the 200-IA-1 Operable Unit (OU) data set that will be used to calculate the sample-specific screening level human health risk evaluation; Document the data processing and data reduction steps taken to prepare the 200-IA-1 OU data set that will be used to identify analytes that could potentially impact groundwater in the future beneath the 200-IA-1 OU representative waste sites; Document the assumptions, equations, and methodologies used to calculate the screening levels for human health cancer risks and noncancer hazards for each representative waste site assigned to the 200-IA-1 OU. Individual measured soil concentrations from 0 to 4.6 m (15 ft) below ground surface (bgs) (shallow vadose zone) are used to calculate the total excess lifetime cancer risk (ELCR) and hazard index (HI) for the outdoor worker scenario to determine if there is a basis for remedial action. Individual measured soil concentrations from the ground surface to the groundwater table are used for the distribution coefficient (Kd) screen to identify analytes that could potentially impact groundwater in the future beneath the 200-IA-1 OU representative waste sites. This ECF supports DOE/RL-2020-51, 200-IA-1 OU Focused Feasibility Study, under the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA). A risk characterization based upon the evaluation of the health risk estimates developed in this ECF will be presented in the focused feasibility study report.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

ComEd Climate Risk and Adaptation Outlook, Phase 1: Temperature, Heat Index, and Average Wind

This Climate Risk and Adaptation Outlook report presents the research and findings of a joint venture between Commonwealth Edison (ComEd) and Argonne National Laboratory (Argonne) to evaluate future climate risks to ComEd’s infrastructure and operations. ComEd recognizes that its position as the state of Illinois’ largest electric utility, serving roughly 70% of the state’s population, underscores the importance for communities across Illinois to consider climate risk as they plan for future conditions. Climate impacts, such as more severe heatwaves or more frequent flood events, can disrupt the generation, transmission, and distribution of electricity and create public health challenges. Taking a proactive approach to adapt to climate risks will help ensure that ComEd continues to serve its growing customer-base reliably and efficiently. This Climate Risk and Adaptation Outlook serves as an important first step to inform ComEd’s grid planning efforts, but Argonne and ComEd recognize that additional research beyond this report will be necessary to characterize future climate conditions more comprehensively throughout northern Illinois, to assess their impacts to grid assets and system operations, and to index effective adaptation options at an asset-level.

24 POWER TRANSMISSION AND DISTRIBUTION↗