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Study of Advanced Occupant Models to Quantify Injury Risk for eVTOL Vehicles

Urban transportation is currently evolving from traditional ground-based vehicles (cars, taxis, and buses) to include air-based electric vertical take-off and landing (eVTOL) vehicles which can be utilized for on-demand transportation, cargo transport, and emergency services. These new eVTOL vehicles are designed to be small, lightweight, and able to operate autonomously without user intervention. Safety is a big part of eventual eVTOL adoption, however gaps in the consideration of safety features exist. Anthropomorphic test devices (ATDs) are used in aerospace crashworthiness standards to quantify occupant injury risk and develop improved safety designs for emergency landing situations, but the ATDs currently used in aircraft certification requirements were developed many decades ago. Developments have occurred over the years involving ATD technology, which includes a host of newer and more biofidelic ATDs such as the Test Device for Human Occupant Restraint (THOR). Increased computing power has also allowed for detailed computational human body models (HBMs) to be created, such as the Global Human Body Model Consortium (GHBMC). This study aims to assess the capability of both HBMs and new ATD designs to identify injury mechanisms within eVTOL relevant emergency landing conditions. Finite element (FE) analysis was used to expand upon full-scale and seat level impact testing conducted by researchers at the National Aeronautics and Space Administration (NASA) to look at effects of occupant model configurations on prediction of injury. The GHBMC HBM and THOR ATD models were simulated in the seat level test conditions to characterize differences between these advanced assessment tools and traditional ATDs in the isolated seat loading environment. Results identified key differences in the responses from each of the models utilized and compared their impact response in head, neck, and spinal injury metrics. The THOR model identified potential risks for head injuries due to head impacts on the seat, however it predicted lower spinal loads than the other occupant surrogates. The GHBMC showed distinctly different biomechanical responses compared to the ATD. The GHBMC model is much more deformable than the ATDs and it exhibited higher distribution of forces and increased sensitivity to the duration of acceleration pulses. Both models incorporated into this study identified key mechanisms for injury that should be considered for passenger safety in the development of these novel aircraft. In addition, this study demonstrated the value of FE modeling for running a variety of complex human surrogates to identify potential injury mechanisms for consideration in regulation and development of new aircraft. Continued research in this field to improve validation these models will only lead to safer aircraft and more comprehensive safety measures.

Crashworthiness↗
DOE OSTI2021

Application of the DNAS framework expansion to occupant population synthesis

Research in occupant behaviour is now using a more elaborate framework of building occupant interaction. Researchers often face challenges in collecting data, particularly for the data to meet the minimum number of required data points and the data interoperability requirements. Researchers address the first issue with the synthetic population and the latter with data ontologies. While synthetic population is commonly used to address the first issue, data ontology development is used to address the latter. The two solutions are complementary to each other. One of the known ontologies in building occupant behaviour research is the Drivers-Needs-Actions-Systems (DNAS) ontology, which has been used by building modelers to describe energy-related occupant behaviour. This paper describes the ontology-based synthetic population generation that can be used in the agent-based modeling (ABM) applications. This paper considers multiple data sources, including ASHRAE Thermal Comfort DB II and IEA Annex 66 data sets. A case study of an office building is used to present the workflow of DNAS framework expansion, synthetic population generation, and agent-based modeling.

Chandra Putra, Handi↗
DOE OSTI2021

Occupancy-Driven Stochastic Decision Framework for Ranking Commercial Building Loads

For effective integration of building operations into the evolving demand response programs of the power grid, real-time decisions concerning the use of building appliances for grid services must excel on multiple criteria, ranging from the added value to occupants' comfort to the quality of the grid services. In this paper, we present a data-driven stochastic decision-support framework to dynamically rank load control alternatives in a commercial building, addressing the needs of multiple decision criteria (e.g. occupant comfort, grid service quality) under uncertainties in occupancy patterns. We adopt a stochastic multi-criteria decision algorithm recently applied to prioritize residential on/off loads, and extend it to i) consider complex load control decisions (e.g. dimming of lights, changing zone temperature set-points) in a commercial building; and ii) systematically integrate zonal occupancy patterns to better identify short-term (and time-varying) opportunities for grid service participation. We evaluate the performance of the proposed framework for curtailment of air-conditioning, lighting, and plug-loads in a multi-zone commercial office building for a range of design choices. With the help of a prototype system that integrates an interactive \textit{Data Analytics and Visualization} frontend we demonstrate a way for the building operators to monitor and change in real-time the available flexibility in energy consumption and to develop trust in the decision recommendations by interpreting the rationale behind the ranking.

Jain, Milan↗
DOE OSTI2020

Quantifying Occupant Health and Productivity for Deep Retrofits: Beyond Traditional IEQ Studies

As energy-efficiency standards for both new construction and existing building renovations become more stringent, further reductions become less tractable and more expensive. With increasing interest and rising investment in healthy built environments, integrating energy efficiency with improved occupant experience (i.e., health, comfort, and work performance) offers a new path to drive deep energy retrofits. However, the difficulty in quantifying and verifying health and productivity gains from building upgrades leads to lower valuation of human benefits in practice. Building codes and standards have progressive energy targets but often give minimum requirements to occupant health for factors such as ventilation and thermal comfort. State and federal laws in the United States that govern the energy service performance contract (ESPC) have no clear and consistent guidance on quantifying non-energy benefits and incorporating them into a formal cost-effectiveness analysis. This paper presents a methodology to measure a building’s potential performance improvement regarding occupant health based on existing evidence correlating IEQ to occupant outcomes. Health improvement measures are integrated with a building energy model to identify and measure the impact of holistic improvement strategies. The net present value of these measures is determined based on the investment costs required to attain those improvements, energy savings, and personnel gains. We will discuss results from one pilot building, which showed nearly $50 per square foot 20-year net present value using the integrated approach.

Keene, Kevin M.↗
DOE OSTI2024

Occupational Radiation Exposure Report for Calendar Year 2023

The U.S. Department of Energy Occupational Radiation Exposure Report for Calendar 2023 presents the results of analyses of occupational radiation exposures at the U.S. Department of Energy (DOE), including the National Nuclear Security Administration (NNSA) operations, during calendar year 2023. This report includes occupational radiation exposure data for over 80,000 DOE Federal employees, contractors, and subcontractors as well as members of the public who have worked in or entered controlled areas monitored for exposure to radiation. DOE publishes this annual report to provide DOE Management, Program Offices, workers, health physicists, and other stakeholders an evaluation of DOE-wide performance regarding compliance with Title 10 of the Code of Federal Regulations (CFR) Part 835, Occupational Radiation Protection (10 CFR 835) radiation exposure limits and adherence to as low as reasonably achievable principles. This report provides a discussion regarding radiation protection and exposure reporting requirements. It also includes calendar year (CY) 2023 information and analyses regarding aggregate, individual, site, DOE Program, transient individuals’ dose, as well as a historical review of DOE exposure data. DOE continues to be diligent in protecting its workers and the public from exposure to radiation from DOE operations as illustrated by the results contained in this report.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

A library of building occupant behaviour models represented in a standardised schema

During the past four decades, a significant body of literature has reported on the impacts of occupant behaviour (OB) on building technologies, operation, and energy consumption. A large number of data-driven behavioural models have been developed based on field data. These models lack standardisation and consistency, leading to difficulties in applications and comparison. To address this concern, an ontology was developed using the drivers-needs-actions-systems (DNAS) framework. Recent work has been carried out to implement the theoretical DNAS framework into an eXtensible Markup Language (XML) schema, titled ‘occupant behaviour XML’ (obXML) which is a practical implementation of OB models that can be integrated into building performance simulation (BPS) programs. This paper presents a newly developed library of OB models represented in the standardised obXML schema format. This library provides ready-to-use examples for BPS users to employ more accurate occupant representation in their energy models. The library, which contains an initial effort of 52 OB models, was made publicly available for the BPS community. As part of the library development process, limitations of the obXML schema were identified and addressed, and future improvements were proposed. Authors hope that by compiling this library building, energy modellers from all over the world can enhance their BPS models by integrating more accurate and robust OB patterns.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Sensitivity of occupant comfort models to humidity and their effect on cooling energy use

Residential building energy consumption in the United States has decreased steadily during the last several decades largely because of advances in building codes as well as voluntary efficiency and labeling programs, which have resulted in the reduction in building sensible loads. Building latent loads have not decreased by the same amount, and field and analytical research studies have concluded that high-efficiency, low-load homes often have elevated indoor humidity levels, possibly leading to occupant discomfort. There are discrepancies in the literature on occupant comfort as it relates to indoor humidity and recommended upper humidity limits. The choice of humidity limit could potentially change results and conclusions on the energy impacts of a new air conditioner or dehumidifier technology, changing ventilation rates, or an improved building envelope. In this study, we use building simulations to explore the impact of humidity control on cooling energy use in efficient residential buildings for different humidity limits. We look at limits based on humidity ratio (or dew point temperature), wet-bulb temperature, relative humidity, and constant slope lines based on the popular comfort models of both Fanger and Gagge. We quantify the additional energy use required to control humidity below these limits. We look at the sensitivity of the results to different temperature and humidity set points, occupant internal gains, moisture buffering levels, evaporator airflow rates, and dehumidifier energy factors. High-efficiency home predicted energy savings are more sensitive to the assumed humidity limit and cooling and dehumidification set points than the other parameters investigated in this paper.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A zone-level occupancy counting system for commercial office spaces using low-resolution time-of-flight sensors

Understanding the locations of occupants in a commercial built environment is critical for realizing energy savings by delivering lighting, heating, and cooling only where it is needed. In this paper, we present an indoor occupancy counting system using a sparse array of inexpensive, low-resolution, and privacy-preserving time-of-flight sensors. We develop and validate an algorithm for zonal occupancy counting that can deal with multiple people walking underneath the sensors in arbitrary directions, and evaluate the system both in realistic simulations of office spaces and in a real-world installation. Finally, we found that our system has an error rate of around 0.4%, resulting in highly accurate person localization and zone counting using only a few sensors per space.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Blood morphology and the levels of selected cytokines related to hematopoiesis in occupational short-term exposure to lead

The aim of the study was to investigate the influence of a short-term exposure to lead on the blood morphology and the levels of selected cytokines related to hematopoiesis in occupationally exposed workers. The study population included 37 males occupationally exposed to lead for 36 to 44 days. Their blood lead level raised from 10.7 ± 7.67 μg/dl at baseline to the level of 49.1 ± 14.1 μg/dl at the end of the study. The level of hemoglobin and values of MCH and MCHC were decreased due to a short-term exposure to lead by 2%, 2%, and 1%, respectively. The counts of WBC, LYM, and MXD increased significantly by 5%, 7%, and 35%. Similarly, the count of PLT increased by 7%, while PDW, MPV, and P-LCR decreased by 6%, 3%, and 9%, respectively. The levels of IL-7, G-CSF, HGF, PDGF AB/BB, SCF, and PECAM-1, decreased significantly by 30%, 33%, 8%, 30%, 25%, and 20%, respectively. A short-term occupational exposure to lead results in a decreased hemoglobin level and increased counts of WBC and PLT. Changes in counts and proportions of different types of leukocytes and decreased values of PLT indices, such as PDW, MPV, and P-LCR, due to the subacute lead-exposure may be associated with lead-induced decreased levels of cytokines related to hematopoiesis, including SCF, G-CSF, IL-7, and PDGF. - Highlights: • Subacute exposure to lead results in a decreased hemoglobin level. • Subacute exposure to lead results in increased counts of WBC and PLT. • Subacute exposure to lead decreases the levels of SCF, G-CSF, IL-7, and PDGF.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Nanotechnology in agriculture: Opportunities, toxicological implications, and occupational risks

Nanotechnology has the potential to make a beneficial impact on several agricultural, forestry, and environmental challenges, such as urbanization, energy constraints, and sustainable use of resources. However, new environmental and human health hazards may emerge from nano-enhanced applications. This raises concerns for agricultural workers who may become primarily exposed to such xenobiotics during their job tasks. The aim of this review is to discuss promising solutions that nanotechnology may provide in agricultural activities, with a specific focus on critical aspects, challenging issues, and research needs for occupational risk assessment and management in this emerging field. Eco-toxicological aspects were not the focus of the review. Nano-fertilizers, (nano-sized nutrients, nano-coated fertilizers, or engineered metal-oxide or carbon-based nanomaterials per se), and nano-pesticides, (nano-formulations of traditional active ingredients or inorganic nanomaterials), may provide a targeted/controlled release of agrochemicals, aimed to obtain their fullest biological efficacy without over-dosage. Nano-sensors and nano-remediation methods may detect and remove environmental contaminants. However, limited knowledge concerning nanomaterial biosafety, adverse effects, fate, and acquired biological reactivity once dispersed into the environment, requires further scientific efforts to assess possible nano-agricultural risks. In this perspective, toxicological research should be aimed to define nanomaterial hazards and levels of exposure along the life-cycle of nano-enabled products, and to assess those physico-chemical features affecting nanomaterial toxicity, possible interactions with agro-system co-formulants, and stressors. Overall, this review highlights the importance to define adequate risk management strategies for workers, occupational safety practices and policies, as well as to develop a responsible regulatory consensus on nanotechnology in agriculture. - Highlights: • Nanotechnology can help precision farming and sustainable agriculture development. • Nano-innovations for agriculture may impact human and environmental health. • Workers exposed to nanomaterials may face emerging occupational risks. • Toxicology should assess the nanomaterial impact on agrosystems and human beings. • Toxicological research may guide effective risk assessment and management processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Determination of solute site occupancies within γ' precipitates in nickel-base superalloys via orientation-specific atom probe tomography

In this study, the analytical limitations in atom probe tomography such as resolving a desired set of atomic planes, for solving complex materials science problems, have been overcome by employing a well-developed unique and reproducible crystallographic technique, involving synergetic coupling of orientation microscopy with atom probe tomography. The crystallographic information in atom probe reconstructions has been utilized to determine the solute site occupancies in Ni-Al-Cr based superalloys accurately. The structural information in atom probe reveals that both Al and Cr occupy the same sub-lattice within the L1 2 -ordered g precipitates to form Ni 3 (Al,Cr) precipitates in a Ni-14Al-7Cr(at.%) alloy. Interestingly, the addition of Co, which is a solid solution strengthener, to a Ni-14Al-7Cr alloy results in the partial reversal of Al site occupancy within g precipitates to form (Ni,Al) 3 (Al,Cr,Co) precipitates. This unique evidence of reversal of Al site occupancy, resulting from the introduction of other solutes within the ordered structures, gives insights into the relative energetics of different sub-lattice sites when occupied by different solutes.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Occupational hygiene in terms of volatile organic compounds (VOCs) and bioaerosols at two solid waste management plants in Finland

Highlights: ► Odorous VOCs: acetic acid, 2,3-butanedione, ethyl acetate, alpha-pinene and limonene. ► VOC concentrations did not exceed occupational exposure limit concentrations. ► 2,3-Butanedione as the health effecting compound is discussed. ► Endotoxin concentrations may cause health problems in waste treatment. - Abstract: Factors affecting occupational hygiene were measured at the solid waste transferring plant at Hyvinkää and at the optic separation plant in Hämeenlinna. Measurements consisted of volatile organic compounds (VOCs) and bioaerosols including microbes, dust and endotoxins. The most abundant compounds in both of the plants were aliphatic and aromatic hydrocarbons, esters of carboxylic acids, ketones and terpenes. In terms of odour generation, the most important emissions were acetic acid, 2,3-butanedione, ethyl acetate, alpha-pinene and limonene due to their low threshold odour concentrations. At the optic waste separation plant, limonene occurred at the highest concentration of all single compounds of identified VOCs. The concentration of any single volatile organic compound did not exceed the occupational exposure limit (OEL) concentration. However, 2,3-butanedione as a health risk compound is discussed based on recent scientific findings linking it to lung disease. Microbe and dust concentrations were low at the waste transferring plant. Only endotoxin concentrations may cause health problems; the average concentration inside the plant was 425 EU/m{sup 3} which clearly exceeded the threshold value of 90 EU/m{sup 3}. In the wheel loader cabin the endotoxin concentrations were below 1 EU/m{sup 3}. High microbial and endotoxin concentrations were measured in the processing hall at the optic waste separation plant. The average concentration of endotoxins was found to be 10,980 EU/m{sup 3}, a concentration which may cause health risks. Concentrations of viable fungi were quite high in few measurements in the control room. The most problematic factor was endotoxins whose average measured concentrations was 4853 EU/m{sup 3}.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Real-Time Fine Grained Occupancy Estimation Using Depth Sensors on ARM Embedded Platforms

Occupancy estimation is an important primitive for a wide range of applications including building energy efficiency, safety, and security. In this paper, we explore the potential of using depth sensors to detect, estimate, identify, and track occupants in buildings. While depth sensors have been widely used for human detection and gesture recognition, computer vision algorithms are typically run on a powerful computer like XBOX or Intel R CoreTM i7 processor. In this work, we develop a prototype system called FORK using off-the-shelf components that performs the entire depth data processing on a cheaper and low power ARM processor in real-time. As ARM processors are extremely weak in running computer vision algorithms, FORK is designed to detect humans and track them in a very efficient way by leveraging a novel lightweight model based approach instead of traditional approaches based on histogram of oriented gradients (HOG) features. Unlike other camera based approaches, FORK is much less privacy invasive (even if the sensor is compromised). Based on a complete implementation, real-world deployment, and extensive evaluation at realistic scenarios, we observe that FORK achieves over 99% accuracy in real-time (4-9 FPS) in occupancy estimation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

FORK: fine grained occupancy estimatoR using kinect on ARM embedded platforms

Occupancy estimation is very useful for a wide range of smart building applications including energy efficiency, safety, and security. In this demonstration, we present a novel solution called FORK, which uses a Kinect depth sensor for estimating occupancy in real-time. Unlike other camera-based solutions, FORK is much less privacy invasive (even if the sensor is compromised) and it does not require a powerful machine like a Microsoft XBOX or an Intel® Core™ i7 processor to process the depth data. Our system performs the entire depth data processing on a cheaper and lower-power ARM processor, in real-time. In order to do that, FORK uses a novel lightweight human model by leveraging anthropometric properties of human bodies for detecting individuals. We will show how FORK detects, tracks, and counts occupants accurately in real-time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Simulation, Challenge Testing and Validation of Solutions for Residential and Commercial Occupancy Sensing/Counting and CO2 Sensing (Final Report)

Carbon dioxide sensors used for monitoring and control applications in buildings are known to be sensitive to long term drift and can be affected by variations in temperature, humidity, other gas interferents, pressure and other factors that cannot be corrected through the typical auto-calibration methods often embedded in the sensor electronics. This investigation was part of the Category D defined in the ARPA-E Saving Energy Nationwide in Structures With Occupancy Recognition (SENSOR) Financial Assistance Funding Opportunity Announcement No. DE-FOA-0001737, FFDA No. 81.135, January 18, 2017. The FOA defined target criteria for the evaluation of the Category C commercial CO2 sensors selected for review and development through the ARPA-E SENSOR program and charged the Iowa State Category D team with developing an evaluation methodology for Category C sensors in accordance with these criteria. As part of the work, the Iowa State team chose to engage the standards community in the development of the evaluation methodology. Standard development work in the D22.05 Indoor Air and D22.03 Ambient Atmospheres and Source Emissions subcommittees of ASTM International Committee D22 on Air Quality on the evaluation of low cost sensors and provision of guidance for using indoor carbon dioxide concentrations to evaluate indoor air quality and ventilation is of particular relevance to the Category D efforts. To date, three draft standards with specific input by the Iowa State Category D team have passed the subcommittee balloting stage and are being balloted in December 2022 and January 2023 in the main D22 committee. In addition to the aforementioned standards to which the PI was a contributing author, intellectual property developed in this project pertaining to “An Automated System for Evaluation of the Long Term Performance of Carbon Dioxide Sensors” and “An Automated Ground Truth System for Real-Time Reliability Assessment, Capture of Control Decisions and Energy Savings Measurements for Occupancy Recognition Systems and Other Applications” are the other major deliverables of the project. These standards and the developed intellectual property are expected to benefit the public in a number of ways stemming from their provision of means to benchmark the performance of carbon dioxide and other sensor systems. In particular, there is high interest in techniques to demonstrate the performance of low-cost carbon dioxide sensors which can be used for typical HVAC applications (e.g., demand controlled ventilation, outdoor and indoor air monitoring, estimation of occupancy, etc.).

42 ENGINEERING↗
DOE OSTI2019

Information Science in Occupational Safety Management

Approaches to information technology in occupational safety management at industrial enterprises are considered. Obstacles to such uses of information technology are noted. Available software and approaches to workplace automation for occupational safety specialists are reviewed. Analysis of the advantages and disadvantages of the available software permits selection of the optimal product for specific problems in occupational safety.

42 ENGINEERING↗
DOE OSTI2022

Motion tomography via occupation kernels

The goal of motion tomography is to recover a description of a vector flow field using measurements along the trajectory of a sensing unit. In this paper, we develop a predictor corrector algorithm designed to recover vector flow fields from trajectory data with the use of occupation kernels developed by Rosenfeld et al. [9,10]. Specifically, we use the occupation kernels as an adaptive basis; that is, the trajectories defining our occupation kernels are iteratively updated to improve the estimation in the next stage. Initial estimates are established, then under mild assumptions, such as relatively straight trajectories, convergence is proven using the Contraction Mapping Theorem. We then compare the developed method with the established method by Chang et al. [5] by defining a set of error metrics. Here, we found that for simulated data, where a ground truth is available, our method offers a marked improvement over [5]. For a real-world example, where ground truth is not available, our results are similar results to the established method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Poster Abstract: Investigating Occupancy Profiles Using Convolutional Neural Networks: Preprint

In this paper, we implement a convolutional neural networks based autoencoder to investigate occupancy profiles. We use the American time use survey data, which contains 191,558 schedules with binary occupancy information. Our results suggest that the trained filters provide an important insight of occupancy profiles (i.e., dominant and distinct patterns), and the latent space compresses the profiles with representative information.

14 SOLAR ENERGY↗