Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “needs assessment”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Reactive transport modeling for supporting climate resilience at groundwater contamination sites

Abstract. Climate resilience is an emerging issue at contaminated sites and hazardous waste sites, since projected climate shifts (e.g., increased/decreased precipitation) and extreme events (e.g., flooding, drought) could affect ongoing remediation or closure strategies. In this study, we develop a reactive transport model (Amanzi) for radionuclides (uranium, tritium, and others) and evaluate how different scenarios under climate change will influence the contaminant plume conditions and groundwater well concentrations. We demonstrate our approach using a two-dimensional (2D) reactive transport model for the Savannah River Site F-Area, including mineral reaction and sorption processes. Different recharge scenarios are considered by perturbing the infiltration rate from the base case as well as considering cap-failure and climate projection scenarios. We also evaluate the uranium and nitrate concentration ratios between scenarios and the base case to isolate the sorption effects with changing recharge rates. The modeling results indicate that the competing effects of dilution and remobilization significantly influence pH, thus changing the sorption of uranium. At the maximum concentration on the breakthrough curve, higher aqueous uranium concentration implies that sorption is reduced with lower pH due to remobilization. To better evaluate the climate change impacts in the future, we develop the workflow to include the downscaled CMIP5 (Coupled Model Intercomparison Project) climate projection data in the reactive transport model and evaluate how residual contamination evolves through 2100 under four climate Representative Concentration Pathway (RCP) scenarios. The integration of climate modeling data and hydrogeochemistry models enables us to quantify the climate change impacts, assess which impacts need to be planned for, and therefore assist climate resiliency efforts and help guide site management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DOE Cold Climate Heat Pump Challenge: Development, Metrics, and Early Field Observations

Space heating in residential buildings is a major contributor of Greenhouse Gas (GHG) emissions in the United States. New, advanced electric heat pumps are poised to provide a low carbon alternative to traditional fossil-based heating, especially in colder climates. Widespread deployment of cold climate heat pumps could help address the significant portion of building emissions and primary energy used in American households, but these gains will require broader acceptance from consumers and decision makers. As part of the “Energy, Emissions, and Equity” (E3) initiative, the U.S. Department of Energy launched the Cold Climate Heat Pump Challenge (CCHP) in 2021 to accelerate the deployment of the next generation of air source heat pumps. The Challenge is currently focused on residential, centrally ducted, electric heat pumps, with a nominal cooling capacity greater than or equal to 24,000 Btu/h (2 tons) and less than or equal to 65,000 Btu/h (5 tons). The Challenge specifications represent a best-in-class heat pump product that provides high-efficiency heating performance in cold climates, employs environmentally friendly low-Global Warming Potential (GWP) refrigerants, and is designed to be grid interactive. Spearheaded by DOE in partnership with the US Environmental Protection Agency (EPA) and Natural Resources Canada (NRCan), the CCHP Challenge brings together numerous major heat pump manufacturers and key stakeholders including utilities and state agencies across the country. In addition to performance testing in a laboratory environment, a key component of this research is evaluating the in-field performance of the prototype heat pumps developed as part of the Challenge. This paper will discuss the development of the CCHP Challenge, key performance specifications, and the energy and non-energy metrics that will be evaluated through the field study. The types of data that are being collected from the units installed in homes across North America as part of the field validation will be described, including details about the sensors and data acquisition system. Data cleaning and analysis methodologies will be discussed, along with early observations from the winter 2022-2023, spring and summer performance periods, and an assessment of non-energy metrics through pre- and post-installation homeowner surveys. Challenges uncovered and lessons learned throughout the process will also be discussed. Finally, the paper will discuss next steps for the second winter assessment period, areas needing additional research, and potential applications of the data collected and analyzed through this work.

Mendon, Vrushali V.↗
DOE OSTI2023

Geographically Dependent Sustainability Indicators for Comparison of Conventional Vegetable Production to Controlled-Environment Agriculture

Many food system lifecycle analyses distill agricultural production and supply chain impacts into single-value sustainability metrics for various food categories. These studies provide an overview of the food supply system that highlight striking results such as the GHG impacts of meat production. The supply chain impacts of vegetable production occupy the middle ground; higher than average food loss and waste, lower than average overall energy use, etc. However, aggregated results obscure the sustainability implications of the location of food production, especially for vegetables. Moreover, the increasing instability of food production systems are not captured, as illustrated by a recent Washington Post article. According to a UC Merced study conducted for the state, California farmers left nearly 400,000 acres of agricultural land unplanted last year because of a lack of water. The result, the study found, was a direct economic cost to farmers of $1.1 billion and the loss of nearly 9,000 agricultural jobs. (The Washington Post, March 21, 2022.) Previous work quantified the food-energy-water nexus implications of transitioning vegetable production from large, centralized agricultural operations to smaller distributed production in controlled-environment farms (CEA). The importance of location-specific data is especially evident for water use. Water impacts of the food system are primarily local to the region where food is produced, water impacts vary significantly between locations, and water stress is a major concern in locations that currently host large agricultural operations. Location-specific data is needed to accurately assess the water impacts of transitioning to CEA. The location of farms in relation to consumers impacts transportation energy use, food loss and waste, and requirements for food processing (e.g., to reduce weight, preserve foods for long storage, and package foods to reduce damage and loss) Reducing transport is particularly relevant for agricultural products that could be grown in CEAs (fruits, vegetables, protein). Access to nutritious food is not evenly distributed in the population. Remote communities, communities in harsh environments, and economically-disadvantaged communities often have poor access to healthy foods. CEA is ideally suited to these environments. However, the energy and water use of CEA, while in many respects lower overall than conventional supply chains, are concentrated within communities and could have significant local impacts. This paper reports on development of sustainability metrics that seek to capture the tradeoffs between the current supply chain and a CEA supply chain for vegetables; focusing on the location-dependent implications of water use, the transition from largely fossil fuel based energy use to electricity, and the food access, resilience and wellbeing implications of urban versus rural food production.

controlled-environment agriculture↗
DOE OSTI2024

Application of Banking Scoring and Rating for Coherent Risk Measures in Electricity Systems ABSCORES

This project developed a framework for asset and system risk management that can be incorporated into current electricity system operations to improve economic efficiency and establish an Electric Assets Risk Bureau. We leveraged scoring and ratings from banking and financial institutions alongside current optimization methods in dispatching power systems to help system operators and electricity markets schedule resources. This approach is based on the observation that there are major discrepancies between the power scheduled by a system operator and the actual power generated/consumed. These discrepancies—exacerbated by unplanned contingencies (e.g., natural disasters)—are caused by multiple factors, including the different financial, environmental and risk preferences of power producers, consumers, and aggregators. We developed a framework that counteracts two failures in electricity system operations: imperfect information and missing markets for products. The technical approach included five tasks. Tasks 1 and 2 supported the development of risk scores at the asset level with historical data collected for this project. Tasks 3, 4, and 5 incorporated scoring into decision-making at the system level. The proposed effort achieved PERFORM's Program Objectives because the proposed outputs and algorithms do not exist in the electricity industry and are an innovative approach to managing risk. Since the acknowledged need to better assess and act upon risk profiles for grid assets has not been met by the industry, this project will also impact ARPA-E's Mission Areas, including improving energy efficiency and giving the U.S. a technological lead in advanced energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Using Calibrated Sodium Data for Preliminary Validation of the SRT Code for Advanced Reactors

Various types of non-light water reactors are currently engaged in the U.S. licensing process. Because of inherent differences compared with well-established large light water reactors, appropriate assessment tools are needed. Specifically, source term analysis, which determines environmental dose impacts from potential accident scenarios, is a crucial part of design and licensing. The U.S. Nuclear Regulatory Commission has emphasized the importance of mechanistic source term analysis for advanced reactor deployments. To align with these needs, Argonne National Laboratory has developed the Simplified Radionuclide Transport (SRT) source term analysis code for metal fuel Sodium-cooled Fast Reactors (SFRs) and microreactors. SRT conducts time-dependent radionuclide transport and retention in SFRs for core and ex-core radionuclide source accident sequences. The main objective of SRT is to provide rapid sensitivity and uncertainty analyses, incorporating parametric uncertainties and summarizing probabilistic results. As part of the code validation process, a study focused on the bubble scrubbing module was performed using an experiment recently carried out by the University of Wisconsin-Madison. Based on the analysis, the modeling approach in SRT provides accurate results for small and large aerosols, while slight underprediction of radionuclide aerosol removal are observed for medium sized aerosols. However, the deviation is minor, considering the highly uncertain phenomenon and range of results, and is in the conservative direction. In addition, uncertainty information derived from the experiments is further implemented, reflecting the actual span of parameters, which leads to enhanced agreement with code predictions. The results demonstrate that SRT provides reasonable predictions for the bubble scrubbing process in sodium pool.

Kam, Dong Hoon↗
DOE OSTI2025

Development and Validation of Two-Phase Flow Models in MOOSE and Application to Molten Salt Reactors

Two-phase flow in Molten Salt Reactors (MSRs) is important as it impacts reactivity evolution, reactor transient response, and the removal of species dissolved in the molten salt through gas phase transfer. Therefore, accurately predicting the gas distribution and the associated liquid-gas interface area in MSRs is essential for their design and operation. Recently, we integrated a new two-phase model into Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE): a multi-D generalization of a mixture drift-flux model. It provides greater computational efficiency, which is typically preferred for modeling reactor transients. However, the mixture model’s accuracy in capturing void distribution and interfacial area in MSRs still needs to be assessed. This article begins with a description of the mathematical framework for the two-phase model implemented in MOOSE. It then presents validation of these models against relevant experimental data. Finally, the model is applied to the Molten Salt Reactor Experiment case study, analyzing various operational conditions such as different rates of fission product volatilization and diverse cover gas entrainment scenarios at the reactor pump. The article concludes by assessing the suitability of the mixture drift-flux model for capturing the two-phase flow dynamics critical to MSR operations

42 - ENGINEERING↗
DOE OSTI2025

Development and Validation of Two-Phase Flow Models in MOOSE for Molten Salt Reactor Application

Two-phase flow in Molten Salt Reactors (MSRs) is important as it impacts reactivity evolution, reactor transient response, and the removal of species dissolved in the molten salt through gas phase transfer. Therefore, accurately predicting the gas distribution and the associated liquid-gas interface area in MSRs is essential for their design and operation. Recently, we integrated two new models into Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE): a multi-D generalization of a mixture drift-flux model and a Euler-Euler model. The Euler-Euler model offers higher fidelity, while the mixture drift-flux model provides greater computational efficiency, which is typically preferred for modeling reactor transients. However, the mixture model's accuracy in capturing void distribution and interfacial area in MSRs still needs to be assessed. This article begins with a description of the mathematical framework for the two-phase models implemented in MOOSE. It then presents validation of these models against relevant experimental data. Finally, both models are applied to the Molten Salt Reactor Experiment case study, analyzing various operational conditions such as different rates of fission product volatilization and diverse cover gas entrainment scenarios at the reactor pump. The article concludes by assessing the suitability of both models for capturing the two-phase flow dynamics critical to MSR operations.

42 - ENGINEERING↗
DOE OSTI2025

Development and Validation of Two-Phase Flow Models in MOOSE and Application to Molten Salt Reactors

Two-phase flow in Molten Salt Reactors (MSRs) is important as it impacts reactivity evolution, reactor transient response, and the removal of species dissolved in the molten salt through gas phase transfer. Therefore, accurately predicting the gas distribution and the associated liquid-gas interface area in MSRs is essential for their design and operation. Recently, we integrated two new models into Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE): a multi-D generalization of a mixture drift-flux model and a Euler-Euler model. The Euler-Euler model offers higher fidelity, while the mixture drift-flux model provides greater computational efficiency, which is typically preferred for modeling reactor transients. However, the mixture model's accuracy in capturing void distribution and interfacial area in MSRs still needs to be assessed. This article begins with a description of the mathematical framework for the two-phase models implemented in MOOSE. It then presents validation of these models against relevant experimental data. Finally, both models are applied to the Molten Salt Reactor Experiment case study, analyzing various operational conditions such as different rates of fission product volatilization and diverse cover gas entrainment scenarios at the reactor pump. The article concludes by assessing the suitability of both models for capturing the two-phase flow dynamics critical to MSR operations.

42 - ENGINEERING↗
DOE OSTI2024

Technical Information Needs and Regulatory Considerations for Front-End Transportation Activities of HALEU Fuel Feed Material

This report fulfills task order number 31310022F0033 Task 1 Assessment of technical information needs and considerations for front-end transportation activities for HALEU fuel feed material. This assessment primarily focuses on the transportation outlook and packaging requirements for transporting high-assay low-enriched uranium (HALEU) fuel feed material. The regulatory framework is described in section 3.0. In section 4.0 the specific issues associated with reviewing HALEU feed material packages are discussed. The rest of the report discusses the need for new packages and Department of Energy progress on HALEU production. Through this evaluation it is shown that the 5% enrichment barrier between low-enriched uranium and HALEU is a significant challenge to transportation packaging. However, there are licensed designs and concepts that can be used to transport HALEU feedstock. No significant issues were identified through the HALEU range up to 20% enriched.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Assessing the Reliability Benefits of Energy Storage as a Transmission Asset

Utilizing energy storage solutions to reduce the need for traditional transmission investments has been recognized by system planners and supported by federal policies in recent years. This work demonstrates the need for detailed reliability assessment for quantitative comparison of the reliability benefits of energy storage and traditional transmission investments. First, a mixed-integer linear programming expansion planning model considering candidate transmission lines and storage technologies is solved to find the least-cost investment decisions. Next, operations under the resulting system configuration are simulated in a probabilistic reliability assessment which accounts for weather-dependent forced outages. The outcome of this work, when applied to TPPs, is to further equalize the consideration of energy storage compared to traditional transmission assets by capturing the value of storage for system reliability.

co-optimization↗
DOE OSTI2020

How Wrong Can the Operational AEP Uncertainty Estimate Be When We Ignore the Correlations Between the Uncertainty Components?

Calculations of wind farm annual energy production (AEP) on operational data are essential for a variety of financial transactions during the life of wind plants. The AEP estimate is associated with an uncertainty value, which is calculated by combining contributions connected to on-site measurements, long-term reference measurements, losses, regression, windiness adjustment, and wind resource interannual variability. Although very limited documentation on the topic exists, the conventional approach currently used by the wind energy community to assess the uncertainty connected to the operational AEP estimate assume that the different uncertainty components are uncorrelated and therefore calculates the overall uncertainty with a sum of squares approach. In this analysis, we contrast the traditional technique to estimate the overall AEP uncertainty by ignoring the correlation between its different components with a novel Monte Carlo based approach, which can instead take into account the correlation between different uncertainty categories. We consider monthly operational data from 472 wind farms from the Energy Information Administration (EIA) 923 database to assess the difference between the two approaches. Long-term wind speed data needed for the AEP assessment are taken from three reanalysis products: the Modern-Era Retrospective analysis for Research and Applications v2 (MERRA-2), the European Reanalysis Interim (ERA-interim), and the National Centers for Environmental Prediction v2 (NCEP-2). The results of the Monte Carlo approach show that three pairs of AEP uncertainty components do show a statistically significant correlation: the uncertainty connected with wind resource inter-annual variability is positively correlated with the one related to the windiness correction and negatively correlated with the one due to the regression, and the wind measurement uncertainty is positively correlated with the regression uncertainty. All these correlations, which are found between uncertainty components which are not only part of an operational analysis, but also of a wind resource assessment, are currently ignored in the conventional techniques used as industry standard. We further investigate the causes of these correlations, in terms of common dependencies of different uncertainty components on wind resource variability, number of data points, and quality of the regression between wind speed and energy production data. Next, we quantify the error in the current industry standard technique, in terms of the percentage difference in total uncertainty calculated with the two considered approaches, for all the analyzed wind farms. We find a mean absolute percentage difference of about 6%, with the largest differences being greater than 20%. The data clearly confirm that ignoring the actual correlation between the uncertainty components can lead to large errors in the assessment of the operational AEP uncertainty, and the proposed Monte Carlo approach should be preferred.

Monte Carlo↗
DOE OSTI2022

An Approach to Dynamic Human Reliability Analysis Using the EMRALD Dynamic Risk Assessment Tool

There is a need for research into dynamic human reliability analysis (HRA) (i.e., simulation- or computation-based HRA), as many researchers have emphasized the importance of applying dynamic approaches to probabilistic safety assessments (PSAs). This study proposes the Procedure-based Investigation Method of EMRALD Risk Assessment – Human Reliability Analysis (PRIMERA-HRA), a dynamic HRA approach based on the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software developed by Idaho National Laboratory (INL). This study suggests how this software can be used to model human actions and evaluate error probabilities. The applicability of this approach is also be investigated in light of an extended loss of AC power (ELAP) scenario. This paper then discusses the major insights derived by comparing this dynamic HRA approach against the static one.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Observations of greenhouse gases as climate indicators

Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO<:sub>2 GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Dashboard for Marine Energy Site Assessment and Monitoring

The marine energy (ME) industry presently relies upon fragmented site assessment solutions that require high resource expenditure for deployment at each site and do not leverage the wealth of readily available tools and information. A wave energy resource assessment dashboard, currently in development, will substantially improve siting, permitting, operations, and maintenance of ME projects by providing an integrated solution that is a one-stop-shop for a developer’s needs. The Site Energy Assessment and MOnitoring Dashboard (SEAMOD) will be of commercial interest to anyone seeking to deploy an ME project and is easily expandable to include tidal and wind energy site assessments. The integrated dashboard is being developed using state-of-the-art database and cloud computing methods and data-assimilative modeling tools that can be coupled with low-cost, rapidly deployable wave buoys and environmental sensing hardware. The combined software and hardware dashboard will reduce wave energy site characterization and wave climate monitoring costs by more than 60 percent and provide assessments that meet international industry standards. To realize a thriving global ME industry, the physical environment at a potential deployment site must be understood, not only for resource characterization, but also for optimization of device and power conversion performance. SEAMOD directly addresses these needs with a commercially marketable product. SEAMOD is a low-cost solution that provides comprehensive ME resource assessments, baseline environmental monitoring, and offshore characterizations required for successful ME development. The key technical objectives for Phase I were a series of software development goals, which when implemented with monitoring solutions, produced an initial proof-of-concept low-cost wave energy resources dashboard. In Phase II, the development of the prototype SEAMOD continued. The basic framework employed was the development of a revised dashboard and monitoring tool customized for ME applications by focusing on IEC site assessment and method requirements. Development was focused on the integration of full hindcast metocean products to provide hindcast resource characterization and environmental information. The final integrated dashboard provides a low-cost solution that delivers comprehensive, scalable, industry-standard energy resource assessments and offshore characterizations required for successful ME development. The integrated dashboard offers visibility of the most recent site modeling, measurements, and historical data. The application and integration of consensus-based standards for wave energy resource assessment, as determined by the International Electrotechnical Commission (IEC), are crucial for the impact and value of SEAMOD. SEAMOD includes monthly, seasonal, and yearly statistics, as well as the total 30-year record, offering temporal resolution of the IEC parameters to aid potential developers in determining the available wave energy resources in their area of interest.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Projections of future climate for U.S. national assessments: past, present, future

Climate assessments consolidate our understanding of possible future climate conditions as represented by climate projections, which are largely based on the output of global climate models. Over the past 30 years, the scientific insights gained from climate projections have been refined through model structural improvements, emerging constraints on climate feedbacks, and increased computational efficiency. Within the same period, the process of assessing and evaluating information from climate projections has become more defined and targeted to inform users. As the size and audience of climate assessments has expanded, the framing, relevancy, and accessibility of projections has become increasingly important. This paper reviews the use of climate projections in national climate assessments (NCA) while highlighting challenges and opportunities that have emerged over time. Reflections and lessons learned address the continuous process to understand the broadening assessment audience and evolving user needs. Insights for future NCA development include (1) identifying benchmarks and standards for evaluating downscaled datasets, (2) expanding efforts to gather research gaps and user needs to inform how climate projections are presented in the assessment (3) providing practitioner guidance on the use, interpretation, and reporting of climate projections and uncertainty to better inform decision-making.

Assessment↗
DOE OSTI2025

Automated segmentation and analysis of point clouds of pier foundations using Pier Inspection and Evaluation Report (PIER)

Pier foundations are commonly used in locations with unstable soil or where other types of foundations are unsuitable or cost prohibitive. A pier foundation consists of vertical columns to support the structure and elevate it above the ground. Common materials for pier foundations include masonry, concrete, timber, and steel. The methods for accurate placement of pier foundations have remained relatively unchanged for decades. For simple installations, construction chalk lines are used to layout the locations of piers to ensure accurate placement and elevation. For more complex installations, surveying instruments operated by trained professionals are employed to accurately locate piers and assess correct elevation before construction. After installation, another survey may need to be performed to assess the quality of the as-built foundation. However, with the advent of terrestrial laser scanners (TLS), the means now exist for contractors to conduct their own assessments of as-built foundations. The major barrier preventing contractors from performing their own assessments of as-built foundation quality is the segmentation and analysis of point cloud data, a skill that often requires a trained user. The objective of this research is to develop a software tool (PIER: Pier Inspection and Evaluation Report) to enable automated segmentation and analysis of point clouds of pier foundations. In this paper, the automated segmentation and analysis algorithms are detailed. A mockup lay out of pier foundations was built using concrete masonry units, and the algorithms were tested to evaluate performance. Limitations of the current algorithms and future research direction are discussed.

Turki, Amine [ORNL]↗
DOE OSTI2020

Integration of ecosystem science into radioecology: A consensus perspective

In the Fall of 2016 a workshop was held which brought together over 50 scientists from the ecological and radiological fields to discuss feasibility and challenges of reintegrating ecosystem science into radioecology. There is a growing desire to incorporate attributes of ecosystem science into radiological risk assessment and radioecological research more generally, fueled by recent advances in quantification of emergent ecosystem attributes and the desire to accurately reflect impacts of radiological stressors upon ecosystem function. This work is a synthesis of the discussions and consensus of the workshop participant's responses to three primary questions, which were: 1) How can ecosystem science support radiological risk assessment? 2) What ecosystem level endpoints potentially could be used for radiological risk assessment? and 3) What inference strategies and associated methods would be most appropriate to assess the effects of radionuclides on ecosystem structure and function? The consensus of the participants was that ecosystem science can and should support radiological risk assessment through the incorporation of quantitative metrics that reflect ecosystem functions which are sensitive to radiological contaminants. The participants also agreed that many such endpoints exit or are thought to exit and while many are used in ecological risk assessment currently, additional data need to be collected that link the causal mechanisms of radiological exposure to these endpoints. Finally, the participants agreed that radiological risk assessments must be designed and informed by rigorous statistical frameworks capable of revealing the causal inference tying radiological exposure to the endpoints selected for measurement.

54 ENVIRONMENTAL SCIENCES↗