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Effect of Personal and Situational Variables on Noise Annoyance: with Special Reference to Implications for En Route Noise

Over 680 publications from 282 social surveys of residents' reactions to environmental noise have been examined to locate 495 published findings on 26 topics concerning non-noise explanations for residents' reactions to environmental noise. This report (1) tabulates the evidence on the 26 response topics, (2) identifies the 495 findings, and (3) discusses the implications for en route noise assessment. After controlling for noise level, over half of the social survey evidence indicates that noise annoyance is not strongly affected by any of the nine demographic variables examined (age, sex, social status, income, education, homeownership, type of dwelling, length of residence, or receipt of benefits from the noise source), but is positively associated with each of the five attitudinal variables examined (a fear of danger from the noise source, a sensitivity towards noise generally, the belief that the authorities can control the noise, the awareness of non-noise impacts of the source, and the belief that the noise source is not important).

Fields, James M.↗

Assessments of Physiology and Cognition in Hybrid-Reality Environments (APACHE)

NASA is planning to return to the Moon in the mid-2020s as a stepping stone to Mars missions in the 2030s. Spacewalks, or extravehicular activities (EVAs), performed on the Moon and Mars will differ in a variety of ways from those that have been performed in decades past. NASA has identified multiple risks to human health and performance associated with a crewed mission to Mars, especially those associated with exploration EVAs which are expected to be a primary mission activity. Crew may be expected to conduct up to 24 hours of EVA per person per week, where the likelihood of injury and/or mental mistakes are increased compared to ground-based training or current microgravity EVAs and the consequences of which can be catastrophic. Current test environments for exploration EVA research and technology development are large, costly facilities that are limited in their availability or capabilities. Spacesuit testing in a reduced gravity environment such as NASA’s Neutral Buoyancy Laboratory, while a good representation of the crew’s physical workload during exploration EVAs, typically has small datasets and is difficult to integrate physiological sensors or other types of crew performance measures. Meanwhile, scientific field-based testing such as NASA’s Desert Research and Technology Studies offers an operationally relevant environment for exploration EVAs, particularly for cognitive workload, but is also limited by small datasets, lack of a pressurized spacesuit, and obtrusive measures. The limitations of current analogs for exploration EVAs identify a need for a new test environment that can approximate both the physical and cognitive demands associated with exploration EVAs to enable rapid, controlled, and repeatable evaluations of human health and performance risks of exploration missions. In response, the Human Physiology, Performance, Protection, and Operations Laboratory (H-3PO) at NASA Johnson Space Center has developed a hybrid reality exploration EVA analog named the Assessments of Physiology And Cognition in Hybrid-reality Environments (APACHE) to address these limitations using a combination of virtual, physical, and hybrid reality techniques. The APACHE facility resides at NASA Johnson Space Center and serves as a large “sandbox” for EVA research and simulation. At its center is a roughly 15x20ft space surrounded by a 14” tall sandbox partially filled with lunar regolith simulant to emulate the physical feeling of walking on a planetary surface and to allow for simulated geology operations. Nearby, a curved passive treadmill (Skillmill Connect, Technogym, Fairfield, NJ) and an omnidirectional treadmill (Infinadeck, Infinadeck, Rocklin, CA) are included to enable exploration of these large virtual environments while also imposing the physical demands, representative timelines, and cognitive burdens required to navigate and traverse these distances during exploration EVA. A 6DOF motion platform is used to simulate rover operations and supports various human performance evaluations and associated risks. Lastly, APACHE can support two extravehicular (EV) crewmembers working in tandem. A computer workstation is located nearby and also supports an intravehicular (IV) crewmember as part of a full mission simulation. The IV crewmember has direct video and audio communication with the EV crew in VR to provide operational and procedural support. The software used in APACHE was created by the JSC Engineering Directorate, in partnership with Buendea, powered by a custom Unreal Engine 5 (UE5.3, Epic Games) project. APACHE currently utilizes the HTC Vive Pro Eye in a wireless configuration for VR simulations. There are two virtual environments that subjects can explore within APACHE, a Lunar and Martian surface. The virtual Lunar surface was created from LIDAR data of the Lunar South Pole to create roughly 16 sq km of explorable terrain. The virtual Martian surface contains roughly 400 sq km of explorable terrain derived from Mars Reconnaissance Orbiter LIDAR data of the Jezero Crater. The immersion and related cognitive burdens of conducting a planetary EVA is simulated through a series of EVA-relevant tasks performed in the VR environment, using these high-fidelity visual representations. Additionally, APACHE includes biosensor driven informatics, such as real-time heart rate monitoring and/or derived values from model simulations, for active monitoring by the EV crew and added cognitive demand. A “Wizard of Oz” control panel enables test operators to activate contingency events such as simulated spacesuit malfunctions, loss of communications, and/or limited visibility. Embedded performance measures such as accuracy, completeness, and execution time have been developed for various exploration tasks to objectively quantify crew performance during an EVA and compare impacts to performance when different environmental stressors, both physical and cognitive, are added to or removed from the simulation. Additionally, validated cognitive and operational performance measures such as the Digit Symbol Substitution Task have been recreated and embedded in VR for direct and relatively unobtrusive measurement of motor perception. The APACHE environment currently supports multiple research studies at NASA. Examples include the CHAPEA project, a series of simulated year-long missions on Mars by a 4-person crew; and the CO2 Contingency Walk Back Study, an investigation of elevated CO2 exposure on crew performance during a contingency EVA scenario. APACHE also provides a test environment to support the development of the Crew State and Risk Model, which is a collection of individualized, mathematical models of crew physical and cognitive state; and the Personalized EVA Informatics and Decision Support system, an operational tool for flight controllers, and eventually a self-reliant Martian crew, to make biomedically-informed decisions in real-time to optimize the EVA planning and execution with respect to crew health and performance. Some technical challenges associated with developing the APACHE environment, as well as current limitations, include VR limitless natural walking with a hybrid spacesuit simulator, optimizing performance for wireless PC VR streaming while maintaining a high degree of visual fidelity, and the integration of various physiological (metabolic masks) and psychometric (eye tracking) sensors with the VR headset.

Human Performance↗

SAGE III/ISS Rapid Data Analysis Through Dashboarding with Jupyter Notebooks

Spaceborne remote sensing observations of Earth’s atmosphere produce significant quantities of data over the life of each mission. In the case of the Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) nearly four years of vertical profiles of atmospheric ozone, water vapor, and nitrogen dioxide concentrations as well as aerosol extinction coefficients have been released. The dichotomy of the desire for both long-term trends in the atmospheric state alongside the assessment of short-term impacts of major disruptive events such as volcanic eruptions and pyrocumulus injections requires agile tools to handle these cases in near real-time as new data are produced. The analysis landscape is further complicated by the desire to compare results between the numerous contemporary observations available for a given dataset. The SAGE III/ISS team has developed a suite of tools leveraging modern web-based frameworks allowing members to interact with a dashboard-style interface to load the data record, assess new profiles as they are generated and in ensemble, compare between species, and additionally add in measurements observed by other platforms as necessary. Leveraging a commonly packaged data format of NetCDF alongside the Python Jupyter Notebook framework, the data can be served to interested parties from an analysis server while still runnable on personal systems if required. This presentation illustrates the ecosystem developed by the SAGE III/ISS team, the applicability to measurements made by any limb-observing platform, and the benefit to transforming routine analyses into readily accessible dynamic plots. Frameworks currently exist at larger scales with projects such as GIOVANNI, and this illustration seeks to show that similar frameworks are accessible and possible within the local research environment while simultaneously unloading human processing cycles for more specialized analysis tasks.

Dashboarding↗

Development and Validation of Algorithms That Analyze Communicating Thermostat Data to Identify Enclosure Retrofit Opportunities

Annual energy savings of up to $\$ 4$ to $\$ 5$ billion could be achieved nationwide through basic insulation and heating system retrofits of existing homes. However, current utility energy efficiency programs are costly and challenging to scale. Customer acquisition occurs primarily through energy bill mailers, mass media, and online advertising that lack specificity about home-specific retrofit opportunities, expected energy savings, and cost-effectiveness. Specific retrofit opportunities are identified via on-site home energy assessments (HEAs) that are inconvenient to homeowners, expensive, and of variable accuracy. We developed computational algorithms that automatically analyze communicating thermostat (CT) heating data that could be used to increase the customer uptake of insulation and air sealing energy conservation measures (ECMs) by identifying homes with the most significant retrofit opportunities, estimating post-retrofit energy savings, and formulating home-specific outreach. The algorithms are based on an extended second-order grey-box model that characterizes a building’s thermal response using lumped elements, coupled with an empirical model of infiltration that accounts for both wind and stack effects. The basic parameters of the model correspond to actual physical parameters of the home, i.e., the home’s overall R-value of and the building envelope ACH50. Unlike the conventional approach, which estimates model parameters based on the best fit to the observed time-dependent room temperature, our approach derives correlations between the daily heating system runtime and temperature difference (indoor-outdoor) that are more robust to data quality issues in real-world applications. We also used HEA data for algorithm development and validation. With the help of our utility partners, Eversource and National Grid, we obtained data sets for hundreds of Massachusetts homes. For each home, these data sets included three sets of information anonymized by the utility: (1) CT data (HVAC runtime, room temperature, and, for some vendors, outdoor temperature and wind speed) collected by the CT vendor (one of three) over a heating season, (2) HEA report performed by the HEA vendor (same vendor for all homes), (3) Monthly utility gas bills coincident with the CT data (3 to 24 per home, depending on availability). For some homes, we also obtained blower-door test results. Initially, we applied the algorithms developed to homes with a single CT and then extended them to homes with two CTs by using an equivalent home approach. Finally, we developed algorithms for prediction of energy savings and a methodology of comparing our predictions with those generated by HEAs. The main technical results indicate that we can reliably identify homes with insulation and/or air sealing retrofit opportunities and provide accurate savings predictions. Our hypothesis is that the algorithms could be applied to utility energy efficiency programs to identify homes that could realize significant energy savings from insulation and/or air sealing retrofits. This information could then be used to reach out to those homes with highly customized outreach, thereby delivering increased program energy savings and cost-effectiveness. This would: Significantly increase the uptake rate of on-site HEAs, and Significantly increase the fraction of HEAs resulting in ECM implementation. To test these hypotheses, we designed and conducted a randomized controlled trial (RCT). The RCT results suggest that personal messaging leads to a two- to five-fold increase in the HEA uptake rate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling Flow and Particle Deposition in a Spent Nuclear Fuel Assembly

CFD (Computational Fluid Dynamic) simulation of aerosol-laden natural convective flow and particle deposition in a spent fuel storage canister with 37 assemblies is currently computationally prohibitive. PWR (Pressurized Water Reactor) assemblies have up to 289 pins or tubes with several spacer grids to align the pins. Spacer grids with mixing vanes induce swirling during operation to increase heat transfer. Each spacer grid contains hundreds of small structures such as retaining clips, channel walls, and openings. The largest canisters store 37 PWR assemblies thus, there are numerous pins, tubes, and spacer grids for which the flow region between and around these structures needs to be determined along with the movement and deposition of aerosol particles. Because of the complicated geometry, modeling the intricate flow even for just one assembly is currently impractical. Nonetheless, we are developing techniques for a practical model to assess the natural aerosol particle deposition process in a canister in the event that a release occurs from one or more fuel pins. In the previous work it was demonstrated that CFD can model the flow through a PWR spacer grid with mixing vanes, including particle deposition, in a reasonable amount of time on a personal computer. In this work, the analysis is extended to include the bypass region between an assembly and the canister basket walls. It is shown that the flow velocity in the bypass region is about three times that of the interstitial region between the pins. The lengths before and after the spacer grid are also extended to determine when the flow becomes fully developed. In addition, the approach of computationally “stitching together” segments of an assembly is demonstrated with the plan to ultimately model a full assembly. The fraction of particles that are deposited in a segment with a spacer grid is determined as a function of particle size and flow velocity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Shared Understanding and Paths Forward for Community Benefit Mechanisms: Workshop Summary Report

On October 7-8, 2024, the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) and the National Renewable Energy Laboratory hosted an in-person workshop focused on research needs and strategies for community benefit mechanisms (CBMs) used in the deployment of renewable energy infrastructure. Community benefit mechanisms (such as community benefit agreements, funds, and donations) are used to provide increased benefits and/or mitigate negative impacts of energy development for the communities that are impacted. The workshop aimed to assess the current state of knowledge, tools, practices, and lessons learned, as well as to identify research and other work needed to improve the impact and effective implementation of CBMs. This report describes the purpose and structure of the workshop and summarizes key themes, questions, issues, and ideas that arose from the workshop.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Vitamin D: Spaceflight, Antarctic, and JSC

Obtaining vitamin D is critical for space travelers because they lack ultraviolet light exposure and have an insufficient dietary supply of vitamin D. Despite the provision of vitamin D supplements to International Space Station (ISS) crewmembers, vitamin D status is consistently lower after flight than before flight, and in several crewmembers has decreased to levels considered clinically significant. Vitamin D has long been known to play a role in calcium metabolism, and more recently its non-calcitropic functions have been recognized. According to the results of several recent studies, functionally relevant measures indicate that the lower limit of serum 25-hydroxyvitamin D (a marker of vitamin D status) should be raised from the current 25 nmol/L to 80 nmol/L. The sub-optimal pre- and postflight vitamin D status is an issue that needs to be addressed, to allow NASA to better define the appropriate amount of supplemental vitamin D to serve as a countermeasure against vitamin D deficiency in astronaut crews. This is very important for long-duration crewmembers, and is critical for exploration-class missions. Ground-based models with limited sunlight exposure could be valuable for evaluating vitamin D supplementation efficacy. One such model is subjects spending the winter in Antarctica, where UV-B radiation levels are zero during the winter. Data from a study of such subjects will enable us to provide long-duration space flight crewmembers with evidence-based recommendations for vitamin D supplementation to achieve optimal vitamin D status before, during, and after flight. We report here results from a vitamin D supplementation study conducted in 2007 in Antarctica at McMurdo Station, and plans for a study to be implemented over the course of 2009. Additionally, in 2008, a study was initiated (and is ongoing) to assess efficacy and safety of supplementing with 2000 IU daily, 10,000 IU weekly, or 50,000 IU weekly for a month and then monthly after that. The data from these studies will enable us to provide space crews with evidence-based recommendations for vitamin D supplementation. The findings also have implications for other persons with limited UV light exposure, including polar workers and the elderly.

Smith, Scott M.↗

Vehicle Design Data Format and Process for a Complete TARIS and OLTARIS Radiation Analysis for Designers and Engineers

Protecting astronauts from space radiation is a complex task when it comes to modeling and simulation. This document shows what information is needed from a spacecraft designer using CAD (Computer-Assisted Design) at each phase of the design to enable the engineers to evaluate the design phase against space radiation limits to determine the suitability of the design for space flight. The current personal exposure limits are listed in NASA STD-3001. A proxy to determine the REID (Radiation Exposure Induced Death) in NASA STD-3001 is the whole body effective dose equivalent (E or effective dose). For short-term tissue effects, organ-averaged gray equivalent (G (sub T)) is used. The TARIS (Tool for the Assessment of Radiation In Space - for LaRC (Langley Research Center) engineers) and OLTARIS (On-Line TARIS) - for designers) systems are used to generate these response functions. The E can use ICRP60 or NASA Q-values. A possible space radiation design basis environment for short-term tissue effects is described and used in all analyses. A single space vehicle was designed with three astronaut configurations and two of those configurations were used in a storm shelter thickness perturbation analysis. Conversion of the data from the CAD model to input necessary for TARIS and OLTARIS is also discussed in detail with relevant examples.

Singleterry, Robert C.↗

Cold sea survival.

Two prototype three-man life rafts were evaluated during the winter months in Arctic waters off Kodiak Island, Alaska, to assess potential survival problems and determine tolerance limits. Each raft incorporated thermal characteristics specifically designed for cold water. Water and air temperatures varied from 0 to +2 C and -5 to +4 C respectively. All subjects were removed upon reaching subjective tolerance. The results showed that none of the clothing assemblies was adequate to maintain a person in comfort even with dry boarding. No significant biochemical shifts in the blood or urine were found. The TUL raft was found to be superior in its thermal characteristics and afforded better subject protection. General tolerance for cold water immersion, wet and dry, and cold water raft exposures are depicted graphically, based on previously reported data.

Veghte, J. H.↗

A PC based fault diagnosis expert system

The Integrated Status Assessment (ISA) prototype expert system performs system level fault diagnosis using rules and models created by the user. The ISA evolved from concepts to a stand-alone demonstration prototype using OPS5 on a LISP Machine. The LISP based prototype was rewritten in C and the C Language Integrated Production System (CLIPS) to run on a Personal Computer (PC) and a graphics workstation. The ISA prototype has been used to demonstrate fault diagnosis functions of Space Station Freedom's Operation Management System (OMS). This paper describes the development of the ISA prototype from early concepts to the current PC/workstation version used today and describes future areas of development for the prototype.

Marsh, Christopher A.↗

Interactive inventory monitoring

Method and system for monitoring present location and/or present status of a target inventory item, where the inventory items are located on one or more inventory shelves or other inventory receptacles that communicate with an inventory base station through use of responders such as RFIDs. A user operates a hand held interrogation and display (IAD) module that communicates with, or is part of, the base station, to provide an initial inquiry. Information on location(s) of the target inventory item is also indicated visibly and/or audibly on the receptacle(s) for the user. Status information includes an assessment of operation readiness and a time, if known, that the specified inventory item or class was last removed or examined or modified. Presentation of a user access level may be required for access to the target inventory item. Another embodiment provides inventory information for a stack as a sight-impaired or hearing-impaired person passes adjacent to that stack.

Spremo, Stevan M.↗

Interactive Inventory Monitoring

Method and system for monitoring present location and/or present status of a target inventory item, where the inventory items are located on one or more inventory shelves or other inventory receptacles that communicate with an inventory base station through use of responders such as RFIDs. A user operates a hand held interrogation and display (lAD) module that communicates with, or is part of the base station to provide an initial inquiry. lnformation on location(s) of the larget invenlory item is also indicated visibly and/or audibly on the receptacle(s) for the user. Status information includes an assessment of operation readiness and a time, if known, that the specified inventory item or class was last removed or examined or modified. Presentation of a user access level may be required for access to the target inventgory item. Another embodiment provides inventory informatin for a stack as a sight-impaired or hearing-impaired person adjacent to that stack.

rfid↗

Activity Time-Use Patterns and Experienced Satisfaction: Travel Behavioral Dynamics from the 2010–2013 American Time-Use Survey Data

Central to the theory of activity-based approaches is the role of time-use and its impacts on various decision processes related to individual activity-travel patterns, thereby determining ones’ daily well-being. This research aims at quantifying and investigating the underlying correlation of time-use and happiness using the repeated cross-section data from the 2010-2013 American Time Use Survey Well-Being module. The survey specifically records reported levels of activity satisfaction as measured through – happiness, meaningfulness, tiredness, sadness and stress experienced from activity participation. Using these scores, we first construct a composite degree of activity satisfaction that a person experiences using latent class cluster analysis. A series of regression models are then estimated to jointly analyze episodic duration and satisfaction separately for each of years from 2010-2013, by controlling for socioeconomics, household lifecycle stages (29-groups based on age, gender, marital status and presence of children), activity characteristics and global life and health assessment measures. Overall, model estimation results reveal a strong negative correlation between episodic duration and happiness from individual activity engagement patterns. This correlation pattern is temporally stable for the years 2010-2013, with minor variations. Results also suggest that household lifecycle stage has a major impact on activity time-use and satisfaction behavior. Further, single parent and younger couples (25 years to 45 years) with children are more likely to engage in longer and less happy episodes due to family commitments. The model findings also show a strong correlation between health conditions and activity happiness.

Ravulaparthy, Srinath↗

Assessments of Physiology and Cognition in Hybrid-Reality Environments (APACHE) – A VR “Sandbox” for Planetary Spacewalk Research

NASA is planning to return to the Moon in the mid-2020s as a steppingstone to Mars missions in the 2030s. Spacewalks, or extravehicular activities (EVAs), performed on the Moon and Mars will differ in a variety of ways from those that have been performed in decades past. NASA has identified multiple risks to human health and performance associated with a crewed mission to Mars, especially those associated with exploration EVAs which are expected to be a primary mission activity. Crew may be expected to conduct up to 24 hours of EVA per person per week, where the likelihood of injury and/or mental mistakes are increased compared to ground-based training or current microgravity EVAs and the consequences of which can be catastrophic. Current test environments for exploration EVA research and technology development are large, costly facilities that are limited in their availability or capabilities. Spacesuit testing in a reduced gravity environment such as NASA’s Neutral Buoyancy Laboratory, while a good representation of the crew’s physical workload during exploration EVAs, typically has small datasets and is difficult to integrate physiological sensors or other types of crew performance measures. Meanwhile, scientific field-based testing such as NASA’s Desert Research and Technology Studies offers an operationally relevant environment for exploration EVAs, particularly for cognitive workload, but is also limited by small datasets, lack of a pressurized spacesuit, and obtrusive measures. The limitations of current analogs for exploration EVAs identify a need for a new test environment that can approximate both the physical and cognitive demands associated with exploration EVAs to enable rapid, controlled, and repeatable evaluations of human health and performance risks of exploration missions. In response, the Human Physiology, Performance, Protection, and Operations Laboratory (H-3PO) at NASA Johnson Space Center has developed a hybrid reality exploration EVA analog named the Assessments of Physiology And Cognition in Hybrid-reality Environments (APACHE)[ to address these limitations using a combination of virtual, physical, and hybrid reality techniques. The APACHE facility resides at NASA Johnson Space Center and serves as a large “sandbox” for EVA research and simulation. At its center is a roughly 15x20ft space surrounded by a 14” tall sandbox partially filled with lunar regolith simulant to emulate the physical feeling of walking on a planetary surface and to allow for simulated geology operations. Nearby, a curved passive treadmill (Skillmill Connect, Technogym, Fairfield, NJ) and an omnidirectional treadmill (Infinadeck, Infinadeck, Rocklin, CA) are included to enable exploration of these large virtual environments while also imposing the physical demands, representative timelines, and cognitive burdens required to navigate and traverse these distances during exploration EVA. A 6DOF motion platform is used to simulate rover operations and supports various human performance evaluations and associated risks. Lastly, APACHE can support two extravehicular (EV) crewmembers working in tandem. A computer workstation is located nearby and also supports an intravehicular (IV) crewmember as part of a full mission simulation. The IV crewmember has direct video and audio communication with the EV crew in VR to provide operational and procedural support.

Human Performance↗

Analyzing Natural Language Context in Human-Machine Teaming using Supervised Machine Learning

Building a foundation for trustworthiness and trust verification in multi-asset teaming is the research challenge of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR). The Design Reference Mission (DRM) for ATTRACTOR is a search and rescue mission objective governed by a multi-member team consisting of human and machine operators. A crucial component to the effort is the communication between humans and autonomous agents throughout both planning and execution stages of the mission. Intuitive communication methods and modalities are posited as critical enablers for certifying trust and trustworthiness. This paper reports on the data collection and analysis conducted in support of the Human Informed Natural-language GANs Evaluation (HINGE)project to attain explainable and trusted communication between human-machine assets. Two identically curated image description datasets were acquired for HINGE, both consisting of two unique input modalities (typed vs. verbal) and retrieved in two distinct contexts (general vs. specific). The gathered datasets were assessed and compared using Parts-of-Speech (POS)features, sentence similarity metrics, and linguistic analysis. Then, the datasets were modeled and tested separately and in combination with one another using machine learning algorithms. The comparison and testing results reveal a superior dataset, by which a preferred context and input is understood, for generating image representations of missing persons using a Generative Adversarial Network (GAN).

Bryan A Barrows↗

Wireless Phone Threat Assessment for Aircraft Communication and Navigation Radios

Emissions in aircraft communication and navigation bands are measured for the latest generation of wireless phones. The two wireless technologies considered, GSM/GPRS and CDMA2000, are the latest available to general consumers in the U.S. A base-station simulator is used to control the phones. The measurements are conducted using reverberation chambers, and the results are compared against FCC and aircraft installed equipment emission limits. The results are also compared against baseline emissions from laptop computers and personal digital assistant devices that are currently allowed to operate on aircraft.

Nguyens, T. X.↗

Recent evolution of risk analyses in atomic bomb survivor studies: new methods and applications

Abstract Several decades ago a dramatic leap forward occurred in the development and application of statistical methods for modeling radiation risk at the Radiation Effects Research Foundation (RERF). Poisson regression analysis for grouped person-year cohort data and the linear excess relative risk model were introduced, and subsequently a devoted software system, Epicure® (https://www.hirosoft.com), was developed by researchers at RERF and at the U.S. National Cancer Institute. Numerous advancements in understanding radiation effects on humans were made possible with these methods, which are still the state-of-the-art for risk assessment at RERF and have remained part of the standard toolbox for radiation—and other environmental—epidemiological studies worldwide. Nevertheless, as our understanding of radiation risk has increased, so have the breadth and depth of questions that require answers based on emerging data that are not amenable to these conventional methods. This overview briefly recounts the conventional methods and then describes our recent diversification into the use or development of new statistical approaches to meet the challenges of burgeoning biological data and emerging mechanistic information. We briefly discuss the development and application of new methods, current and planned, that are part of the RERF Statistics Department’s role in supporting institution-wide research, especially in our collaborations involving the Life Span Study, Adult Health Study, and First-generation Offspring Clinical Study. Some approaches to modeling and assessing radiation risk with newer methods mentioned herein have already been published, while some are still in development or are only beginning at the proposal stage.

Oncology↗

False Indications of Dose-Response Nonlinearity in Large Epidemiologic Cancer Radiation Cohort Studies; A Simulation Exercise

This study explores the likely prevalence of false indications of dose-response nonlinearity in large epidemiologic cancer radiation cohort studies (A-bomb survivors, INWORKS, Techa River). Reasons: Increasing numbers of tests of nonlinearity are being made in studies. Hypothesized nonlinear dose-response models have been justified to policy makers by analyses that rely in part on isolated findings that could be statistical fluctuations. After removing dose nonlinearity (linearization) by adjusting person-years of observation at each dose category, indications of nonlinearity, necessarily false, were counted in 5,000 randomized replications of six datasets. The average frequency of any false positive for five indicators of nonlinearity tested against a linear null was roughly 25% in Monte Carlo simulations per study, consistent with binomial calculations, increasing to ~50% within 6 studies assessed. Comparable frequencies were found using Akaike's information criterion (AIC) for model selection or multi-model averaging. False above-zero threshold doses were found more than 50% of the time, averaging to 0.05 Gy, consistent with findings in the 6 studies. Such bias, uncorrected, could distort meta-analyses of multiple studies, because meta-analyses can incorporate high P value findings. AIC-based correction for the extra threshold parameter lowered these false occurrences to 8 to 19%. Given the simulation rates, the possibility of false positives might be noted when isolated findings of nonlinearity are discussed in a regulatory context. When reporting a threshold dose with a P value > 0.05, it would be informative to note the expected high false prevalence rate due to bias.

62 RADIOLOGY AND NUCLEAR MEDICINE↗