SEARCH · Engineering Papers
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.
This case study describes an advanced lighting controls replacement project across multiple healthcare facilities, recognized as part of DOE's Integrated Lighting Campaign.
Exoskeletons have evolved from early medical prototypes to advanced systems capable of addressing physical demands in various industries. This report explores the potential of active exoskeleton technology within the utility sector, focusing on its application for linemen who face significant risks of work-related musculoskeletal disorders (WMSDs). By analyzing existing literature on exoskeletons across industries such as construction, manufacturing, and military, the study identifies a gap in utility-specific applications. Task-specific design features like gravity compensation, limb support, and advanced safety measures, improve exoskeletons’ potential to alleviate physical strain, reduce workplace injuries, and enhance productivity. This review emphasizes the need for targeted research and development to optimize exoskeleton designs for the utility sector to provide benefits for workers, companies, and the broader community.
Niowave Inc. produces medical radioisotopes within the US. Lead-bismuth eutectic (LBE) is irradiated using an electron beam to produce neutrons that are used in the production of Molybdenum-99 (Mo-99). The medical community relies on a steady supply of Mo-99 which is primarily used in medical diagnostic imaging. The irradiation of LBE results in high temperatures within the molten metal, this work focusses on the design of ancillary systems associated with the liquid metal system. The LBE is initially at a temperature of 200°C and flows over a steel plate to create a waterfall. The electron beam is then aimed at the waterfall to generate neutrons. The peak temperatures of the LBE post irradiation depend on the beam energy of the LINAC. For a 15 MeV and 20 kW beam, the temperatures can range between 300°C and 350°C. The LBE is cycled through the system to create a closed loop that requires the post-irradiation LBE to be cooled back to 200°C. This work focuses on the heat exchanger and condenser system responsible for the cooling of the post-irradiation LBE.
The Vision Zero-Safe Systems Approach prioritizes fast access to Emergency Medical Services (EMS) to improve the survivability of road users in transportation crashes, especially concerning the recent increase in pedestrian-involved crashes. Pedestrian crashes resulting in immediate or early death are considerably more severe than those taking longer. The time gap between injury and fatality is known as survival time, and it heavily relies on EMS response time. The characteristics of the crash location may be associated with EMS response and survival time. A US Department of Transportation initiative identifies communities often facing challenges. Six disadvantaged community (DAC) indicators, including economy, environment, equity, health, resilience, and transportation access, enable an analysis of how survival and EMS response times vary across DACs and non-DACs. To this end, this study created a unique and comprehensive database by linking DACs data with 2017–2021 pedestrian-involved fatal crashes. This study utilizes two-stage residual inclusion models with segmentation for DACs and non-DACs accounting for the endogenous relationship between EMS response and pedestrian survival time. The results indicate that EMS response time is higher and pedestrian survival time is lower in DACs than in non-DACs. A delayed EMS response time is associated with a greater reduction in survival time in DACs compared to non-DACs. Factors, e.g., nighttime and interstate crashes, contribute to higher EMS response time, while pedestrian drugs, driver speeding, and hit-and-run behaviors are associated with a greater reduction in survival time in DACs than non-DACs. Finally, the implications of the findings are discussed in the paper.
This tutorial paper focuses on safe physics-informed machine learning in the context of dynamics and control, providing a comprehensive overview of how to integrate physical models and safety guarantees. As machine learning techniques enhance the modeling and control of complex dynamical systems, ensuring safety and stability remains a critical challenge, especially in safety-critical applications like autonomous vehicles, robotics, medical decision-making, and energy systems. We explore various approaches for embedding and ensuring safety constraints, including structural priors, Lyapunov and Control Barrier Functions, predictive control, projections, and robust optimization techniques. Additionally, we delve into methods for uncertainty quantification and safety verification, including reachability analysis and neural network verification tools, which help validate that control policies remain within safe operating bounds even in uncertain environments. The paper includes illustrative examples demonstrating the implementation aspects of safe learning frameworks that combine the strengths of data-driven approaches with the rigor of physical principles, offering a path toward the safe control of complex dynamical systems.
Bias in medical image segmentation can lead to unequal performance across demographic subgroups, raising concerns about fairness and reliability in clinical AI systems. While deep learning models have achieved high segmentation accuracy, ensuring equitable performance across race and gender remains a significant challenge, particularly in privacy-sensitive healthcare environments. This study investigates fairness-aware medical image segmentation for hip and knee radiographs using deep learning models evaluated in both centralized and Federated Learning (FL) settings. We introduce Curriculum Learning (CL) strategies and Progressive Loss (PL) functions to regulate sample difficulty during training. In addition, we propose two novel fairness-oriented federated learning algorithms, Federated Intersection over Union (FedIoU) and Federated Intersection over Union with Outlier Analysis (FedIoUoutlier). Experiments are conducted using multiple segmentation backbones and simulated multi-site data partitions derived from the Osteoarthritis Initiative dataset. Model performance is evaluated using Intersection over Union (IoU), IoU standard deviation, Skewed Error Ratio (SER), and Min-Max Disparity across race and gender subgroups. Statistical significance was verified using paired t-tests to compare per-sample IoU performance against baseline configurations. Across both hip and knee segmentation tasks, curriculum learning and progressive loss strategies consistently improved segmentation accuracy and reduced demographic performance disparities in centralized training. In federated settings, fairness-aware aggregation further enhanced performance. Notably, FedIoUoutlier combined with balanced curriculum learning and tiered progressive loss achieved the highest mean IoU while yielding the lowest SER and Min-Max Disparity, indicating improved fairness without sacrificing accuracy. In several configurations, federated models matched or exceeded the performance of optimized centralized models, with statistically significant improvements in per-sample IoU over baseline configurations. The results demonstrate that structured training strategies and fairness-aware federated aggregation can jointly improve accuracy, stability, and demographic fairness in medical image segmentation. By integrating curriculum learning, progressive loss, and novel FL algorithms, this work provides a practical pathway toward equitable and privacy-preserving AI systems for medical imaging.
Tritium (T 2 ) is a radioactive isotope of hydrogen that is produced in nuclear fission reactions and is often used in nuclear fusion reactions and accelerator-based applications for medical isotope production. As a hydrogen isotope, tritium can readily bind to hydroxyl radicals (OH), forming tritiated water (HTO or T 2 0), and to carbon atoms. Tritium decays to helium-3 ( 3 He) via beta-decay with max decay energy of 18.6 keV. While it is not an external radiation hazard, it can be an internal radiation hazard if tritium is inhaled, ingested, or absorbed through the skin. In applications where tritium is handled, tritium confinement is performed using different barriers to minimize releases to the environment. For gaseous (elemental), liquid (oxide), and metal (hydride) tritium, process piping and components provide the primary confinement function. Secondary tritium confinement is typically provided by inert (i.e. non-flammable gases such as nitrogen, argon, or helium) gloveboxes which are connected to a tritium stripper system. Primary tritium confinement barriers typically produce low volumes of high tritium concentrations of tritiated methane from carbon in steels or organic materials along with tritiated water/tritium oxide (e.g. HTO) and tritiated ammonia from reactions with oxygen and nitrogen. Tritium escaping primary confinement into secondary confinement atmospheres (e.g. gloveboxes) produce higher volumes of lower activity contamination than found in process piping. Tritium contamination also occurs by leaks or tritium permeation/diffusion through confinement materials. Tritium from inside primary confinement barriers will diffuse or leak out of the primary confinement barrier and usually into the air, if the system is inside an air hood or ventilated hot cell, or into the secondary confinement (e.g. glovebox) atmosphere which is either exhausted or stripped based on the function of the secondary confinement (glovebox) system. Accelerator based processes for medical isotope production represent an atypical tritium contamination challenge. In medical isotope production, deuterium supply gas is ionized and accelerated to a tritium gas target to produce neutrons that are then used to produce the medical isotopes through additional nuclear fission reactions. To create large voltage differentials for accelerator operations, an electrical insulation medium is needed to prevent or rapidly quench electric discharges. A common electrical insulation medium utilized in accelerator applications is sulfur hexafluoride (SF 6 ) gas. SF 6 has a high dielectric strength and allows for the construction of smaller accelerator systems compared to other electrical insulation mediums such as air or dry nitrogen. Due to tritium permeation/diffusion through accelerator process and confinement materials, there is the possibility that tritium can contaminate the electrical insulation medium of the accelerator. Tritium contaminated SF 6 creates a material without any obvious processes for managing the contamination, reuse, or disposal of the used SF 6 . This document will discuss possible management strategies for tritium contaminated SF 6 for accelerator-based processes for Molybdenum-99 (Mo-99) production.
In a large hospital system, a network of hospitals relies on electronic health records (EHRs) to make informed decisions regarding their patients in various clinical domains. Consequently, the dependability of the health information technology (HIT) systems responsible for collecting EHR data is of utmost importance for patient safety. Recently, novel methods and tools aimed at identifying anomalies in EHR data to bolster the reliability of HIT systems have been introduced. However, these existing methods and tools primarily concentrate on individual hospitals, which limits our understanding of system-wide anomalous events and their potential impact on patient safety across multiple hospitals. In this article, we introduce a new approach to detecting anomalies in EHR data within a network of hospitals. This is achieved by combining advanced machine learning techniques with graph algorithms to create a tool capable of swiftly identifying and responding to deviations. Our proposed approach employs a combination of five machine learning models, harnessing the unique strengths of each model to provide a more robust detection system. The detected anomalies are then represented as graphs, allowing us to recognize patterns across the hospital network. This aids in identifying anomalies that span multiple medical facilities, potentially indicating broader system-level risks. Extensive real-world testing of our approach demonstrated its ability to offer actionable insights compared to existing methods. Additionally, its scalable design ensures seamless integration into existing HIT infrastructures.
Disclosed herein are various medical device components, including components that can be incorporated into robotic and/or in vivo medical devices. Also disclosed are various medical devices for in vivo medical procedures. Included herein, for example, is a surgical robotic device having an elongate device body, a right robotic arm coupled to a right shoulder assembly, and a left robotic arm coupled to a left shoulder assembly.
Disclosed herein are various medical device components, including components that can be incorporated into robotic and/or in vivo medical devices. Also disclosed are various medical devices for in vivo medical procedures. Included herein, for example, is a surgical robotic device having an elongate device body, a right robotic arm coupled to a right shoulder assembly, and a left robotic arm coupled to a left shoulder assembly.
Scintillators with faster timing capabilities are currently in high demand for use in radiation detection systems in the fields of nuclear and medical physics. The limited number of suitable materials that meet the performance criteria of next generation detection systems presents an opportunity for discovery of new fast scintillator materials. In this work, the effects of doping several ultrafast core-valence luminescent (CVL) scintillators with divalent Zn is explored. Three compounds are investigated – CsMgCl 3 , Cs 2 MgCl 4 , and Cs 3 MgCl 5 – and single crystals of each doped with 5 mol% Zn are grown via the Bridgman method. Additionally, mixing across the full range of concentrations (from 0 % to 100 % Zn) is explored in the Cs 2 Mg 1-x Zn x Cl 4 and Cs 3 Mg 1-x Zn x Cl 5 systems. For low concentrations of Zn, light yields of all three compounds are enhanced (by up to ~60 %) compared to the pure crystals, achieving what we believe to be the brightest known CVL, CsMgCl 3 :Zn 5 % (3400 ± 170 ph/MeV light yield). More importantly, Zn doping does not affect the ultrafast timing properties, with each composition maintaining a single-component decay time around 1–3 ns. A sub-100 ps coincidence time resolution (CTR) is also achieved with CsMgCl 3 :Zn 5 %. The results of this work reveal a new avenue towards obtaining brighter CVL materials, which could open up possibilities for more advanced ultrafast scintillators to be discovered moving forward.
This work will discuss evaluation and design of new and modified facility level radiological containment, transfer, and handling systems in support of the United States’ American Medical Isotope Production Act. In the United States alone, Molybdenum-99 (Mo-99) is used as a precursor to locally generate its decay product, technetium-99m (Tc-99m), for use in approximately 40,000 medical procedures every day to detect cancer and heart disease. Currently, however, Mo-99 is primarily produced overseas and typically requires highly enriched uranium (HEU) which is classified as weapon -usable. This poses a serious security risk to the United States and, in 2012, Congress passed the American Medical Isotope ACT which aimed to cease all Mo-99 production that requires HEU and support American based companies who have found safer production methods. Through this effort, a system was designed and developed to access irradiated material in processing hot cells for ease of material introduction and removal in the confined area. The proposed solution uses a double-door design that allows for easy access to material while also providing shielding through a mechanically manipulated carousel. A system was also designed to transport irradiated materials from target reactors to a target receipt box using a rail guide system, pneumatic motor, and lead screw drive.
Abstract The growing need for the implementation of stretchable biosensors in the body has driven rapid prototyping schemes through the direct ink writing of multidimensional functional architectures. Recent approaches employ biocompatible inks that are dispensable through an automated nozzle injection system. However, their application in medical practices remains challenged in reliable recording due to their viscoelastic nature that yields mechanical and electrical hysteresis under periodic large strains. Herein, we report sponge-like poroelastic silicone composites adaptable for high-precision direct writing of custom-designed stretchable biosensors, which are soft and insensitive to strains. Their unique structural properties yield a robust coupling to living tissues, enabling high-fidelity recording of spatiotemporal electrophysiological activity and real-time ultrasound imaging for visual feedback. In vivo evaluations of custom-fit biosensors in a murine acute myocardial infarction model demonstrate a potential clinical utility in the simultaneous intraoperative recording and imaging on the epicardium, which may guide definitive surgical treatments.
Rapid developments in machine vision technology have impacted a variety of applications, such as medical devices and autonomous driving systems. These achievements, however, typically necessitate digital neural networks with the downside of heavy computational requirements and consequent high energy consumption. As a result, real-time decision-making is hindered when computational resources are not readily accessible. Here we report a meta-imager designed to work together with a digital back end to offload computationally expensive convolution operations into high-speed, low-power optics. Further, in this architecture, metasurfaces enable both angle and polarization multiplexing to create multiple information channels that perform positively and negatively valued convolution operations in a single shot. We use our meta-imager for object classification, achieving 98.6% accuracy in handwritten digits and 88.8% accuracy in fashion images. Owing to its compactness, high speed and low power consumption, our approach could find a wide range of applications in artificial intelligence and machine vision applications.
Rapid advances in deep learning have led to paradigm shifts in a number of fields, from medical image analysis to autonomous systems. These advances, however, have resulted in digital neural networks with large computational requirements, resulting in high energy consumption and limitations in real-time decision-making when computation resources are limited. Here, we demonstrate a meta-optic–based neural network accelerator that can off-load computationally expensive convolution operations into high-speed and low-power optics. In this architecture, metasurfaces enable both spatial multiplexing and additional information channels, such as polarization, in object classification. End-to-end design is used to co-optimize the optical and digital systems, resulting in a robust classifier that achieves 93.1% accurate classification of handwriting digits and 93.8% accuracy in classifying both the digit and its polarization state. This approach could enable compact, high-speed, and low-power image and information processing systems for a wide range of applications in machine vision and artificial intelligence.
A beam accelerator system operable to produce a medical isotope, including an ion accelerator that generates an ion beam; a low-pressure chamber; an anode adjacent and fluidly connected to the low-pressure chamber; a plasma window adjacent and fluidly connected to the anode; and a cathode housing adjacent and fluidly connected to the plasma window. The plasma window has a plurality of plates, each plate having an aperture that is aligned with an aperture in one or more adjacent plates to form a plasma channel. One or more plates in the plurality of plates includes a unitary plate having an aperture therein, and one or more cooling channels entering the unitary plate at a first side of the unitary plate and exiting the unitary plate at a second side of the unitary plate. The one or more cooling channels run through a thickness of the unitary plate.
Abstract Wildfire smoke is associated with short-term respiratory outcomes including asthma exacerbation in children. As investigations into developmental wildfire smoke exposure on children’s longer-term respiratory health are sparse, we investigated associations between developmental wildfire smoke exposure and first use of respiratory medications. Prescription claims from IBM MarketScan Commercial Claims and Encounters database were linked with wildfire smoke plume data from NASA satellites based on Metropolitan Statistical Area (MSA). A retrospective cohort of live infants (2010–2016) born into MSAs in six western states (U.S.A.), having prescription insurance, and whose birthdate was estimable from claims data was constructed ( N = 184,703); of these, gestational age was estimated for 113,154 infants. The residential MSA, gestational age, and birthdate were used to estimate average weekly smoke exposure days ( smoke-day ) for each developmental period: three trimesters, and two sequential 12-week periods post-birth. Medications treating respiratory tract inflammation were classified using active ingredient and mode of administration into three categories:: 'upper respiratory', 'lower respiratory', 'systemic anti-inflammatory'. To evaluate associations between wildfire smoke exposure and medication usage, Cox models associating smoke-days with first observed prescription of each medication category were adjusted for infant sex, birth-season, and birthyear with a random intercept for MSA. Smoke exposure during postnatal periods was associated with earlier first use of upper respiratory medications (1–12 weeks: hazard ratio (HR) = 1.094 per 1-day increase in average weekly smoke-day, 95%CI: (1.005,1.191); 13–24 weeks: HR = 1.108, 95%CI: (1.016,1.209)). Protective associations were observed during gestational windows for both lower respiratory and systemic anti-inflammatory medications; it is possible that these associations may be a consequence of live-birth bias. These findings suggest wildfire smoke exposure during early postnatal developmental periods impact subsequent early life respiratory health.
Flat-flex assemblies are widely used across a diverse range of technologies, including consumer electronics, automotive systems, aerospace and defense applications, and medical devices, due to their compact form factor and flexibility. However, environmental stressors like temperature and humidity are known to degrade performance over time, though the main mechanisms for degradation remain unknown. Here, in this work, we examined the aging behavior of copper/polyimide/adhesive laminate systems under varying temperature and humidity conditions, focusing on material degradation and its effects on mechanical and dielectric properties. Results show that peel strength and breakdown voltage decrease with exposure time, temperature, and humidity; spectroscopic characterization revealed that the adhesive, and not the polyimide, is the weak link in the material stack-up. The adhesive, identified as a butyl acrylate-acrylonitrile (BA-AN) copolymer, exhibited age-related spectral changes that correlated with exposure severity and duration. Hydrolysis at BA ester and AN nitrile groups was identified as the primary degradation mechanism, producing amides, acids, and alcohols. We developed a mechanistic model that connects kinetic parameters for BA-AN spectral band decay to peel strength and breakdown voltage, and implicates hydrolysis at the AN moiety, not BA, in performance decrements. Modeling predictions at ambient conditions indicate faster decline in peel strength than dielectric strength at early times, followed by plateauing of both properties at longer times. These findings provide critical insights into laminate aging mechanisms and highlight the importance of addressing BA-AN degradation to improve the long-term reliability of these systems in high-humidity environments.