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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.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

What's in a Name? Developing a Standardized Taxonomy for HVAC System Faults

Faults occurring in heating, ventilation and air-conditioning (HVAC) systems have significantly negative impacts on building energy consumption, occupant comfort, and indoor air quality. In the past thirty years, extensive research has been conducted on fault detection and diagnostics (FDD) methods, and there are now dozens of commercially available FDD software tools. Growing adoption of FDD tools has the potential to generate a massive and useful data set on fault characteristics. However, the lack of a unifying taxonomy is a significant barrier to efficient analysis and evaluation of FDD outputs. Therefore, there is a strong need to develop a robust taxonomy which can better represent and interpret FDD output data. This paper documents the development of a unifying taxonomy for HVAC system faults in commercial buildings, with initial focus on air handling units, variable air volume terminal units, and roof top unit systems. The developed fault taxonomy employs both a physical hierarchy of HVAC equipment and a cause-effect relationship model as tools to better understand and support root cause analysis for HVAC faults. A variable air volume terminal unit is used as an example to demonstrate the application of the developed fault taxonomy. The taxonomy has short-term application in a major U.S. study on fault prevalence, and promises longer term benefits to FDD software developers and building operators by creating a foundation for improved approaches to identifying and resolving HVAC faults.

Chen, Yimin↗
DOE OSTI2024

“Production of High Specific Activity 155 Tb, 161 Tb and 203 Pb for Research and Clinical Applications: Effective Target Design, Target Material Recycling and Radioisotope Separation”

Radioisotopes are essential for the development and application of radiopharmaceuticals that target specific diseases, such as cancer, offering unique potential for precision medicine. The growing demand for theranostic radioisotopes underscores their critical role in personalized medicine, where they enhance diagnostic imaging, minimize patient radiation exposure, and improve targeted tissue uptake, particularly in receptor- and antigen-directed therapies. The theranostic pair terbium-155 (diagnostic) and terbium-161 (therapeutic) holds significant promise for advancing individualized, targeted, and dosimetry-driven radiotherapies. However, the United States currently lacks routine and reliable production of these isotopes. This project made significant progress toward addressing this supply issue by developing production and separation methods for terbium-155 and terbium-161 while also training the next generation of the nuclear and radiochemistry workforce. This grant also strengthened collaboration between scientists at the University of Washington, the University of Missouri and Brookhaven National Laboratory. The research effort focused on evaluating target preparation methods, optimizing irradiation parameters, and refining isolation processes. In addition, the project provided extensive hands-on training to graduate students and postdoctoral fellows, equipping them with expertise in radioisotope production technologies and fostering the growth of the nuclear science workforce.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

A bi-level data-driven framework for fault-detection and diagnosis of HVAC systems

Long-term operation of heating, ventilation, and air conditioning (HVAC) systems will eventually lead to a range of HVAC system failures, resulting in excessive energy consumption and maintenance costs. Here, to avoid HVAC malfunctioning, fault detection diagnostic (FDD) is utilized as a common practice. Machine learning methods have lately received considerable interest for FDD analysis of HVAC systems due to their high detection accuracy. Meanwhile, HVAC malfunctions are regarded as rare occurrences, hence normal operating data samples are much more accessible than data samples in faulty and malfunctioning conditions. The dominating frequency of normal operation in HVAC datasets has also led to heavily biased classification algorithms within the literature. Moreover, the focus of previous literature has been on increasing the accuracy of the models which leads to a high number of false positives (misleading alarms) in the system. In order to enhance the performance of diagnostic procedures and fill the mentioned gaps, this study proposes a novel data-driven framework. A bi-level machine learning framework is developed for diagnosing faults in air handling units (AHUs) and rooftop units (RTUs) based on principal component analysis (PCA), time series anomaly detection, and random forest (RF). It is shown that PCA can reduce the dataset dimension with one principal component accounting for 95% of data variance. Also, the random forest could classify the faults with 89% precision for single-zone AHU, 85% precision for RTU, and 79% for multi-zone AHU. By proposing this framework, three persistent challenges are addressed: (I) minimizing false positives; (II) accounting for data imbalance; and (III) normal condition monitoring of equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Magnetic Designs of New First Target Beamline Magnets for the ORNL SNS Upgrade

The Spallation Neutron Source (SNS) at ORNL currently is being upgraded from 1.0 GeV to 1.3 GeV. Several water-cooled magnets should be upgraded to transport 30% of higher beam energy. New chicane, injection/extraction septum, and Lambertson magnets were designed. Designing the magnets was a challenging task because the new magnets required good combined integrated field quality and needed to occupy the old magnets space but with about 20% greater integrated magnetic field. Additional strong requirements applied to the magnets fringe field do not disturb the circulating beam. The special field profiles had to be provided in foil areas between magnets. The analysis described here was based on OPERA3D simulations. A special technique was used for analyzing the integrated field harmonics. Initially, the particle track was simulated, and integrated field components were calculated along this track for the reference radius, which were used for the harmonics analysis. In addition, 3D field maps were provided for beam optics simulations. The final beamline analysis confirmed good beam transmission and low losses.

3d field maps↗
DOE OSTI2025

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Performance Results for Sensor Assignment Problem as Solved on a Multi-Node Cluster

An earlier report described a procedure for optimal sensor set selection and its implementation on a computational cluster. This new and innovative capability was developed to facilitate a reduction in operations staffing levels to improve plant economics. By automating surveillance and maintenance tasks through early detection of degrading sensors and equipment, staff can be more efficiently deployed. The method uses automated reasoning and domain knowledge in the form of the conservation equations to infer from plant measurements the state of equipment health. Inclusion of domain knowledge addresses the problem that exists with pure data-driven methods that there are no rigorous guidelines for determining what constitutes an adequate sensor set. Formalizing the procedure for sensor set selection as we have done results in a more reliable and explainable diagnosis of plant equipment health. Importantly, from the standpoint of the plant owner, personnel are provided with an early and explicit diagnosis of an equipment problem. That in principle automates the process and eliminates having to send personnel into the plant to find the cause as typically occurs when a data-driven method detects an anomaly. In this report we describe first results obtained using a computational cluster to solve the sensor set selection problem as framed above. The case described addresses the problem of equipment health monitoring in the high-pressure (HP) feedwater system of a pressurized light water reactor as seen through the eyes of our collaborating utility partner. Maintenance of this system can amount to millions of dollars per year if equipment health issues go undiagnosed and lead to loss of function. On examining the potential that is inherent in the installed sensor set for diagnosing equipment health degradation, it was found that greater fault resolution capability can be achieved using a sensor set that is 20 percent fewer in number. The take-away is that compared to the installed sensor set there exists a more strategic assignment of sensors that will furnish better health monitoring capability and with fewer sensors. Where the problem defies solution by manual inspection, as is the case here, one can be found by an algorithm. The solution was obtained in four hours using 30 computational cores. The HP feedwater problem as posed above illustrates the added value of approaching the sensor selection problem as one amenable to algorithmic solution. This problem is of interest to advanced reactor designers and to utilities that are setting up remote monitoring and diagnostic centers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A development of wide dynamic-range halo monitor for 8 GeV proton beams at FNAL

The FNAL accelerator complex has been upgrading in increasing beam intensity and beam quality. A new beam halo diagnostic device is required in the beam transport line between booster and Recycler. For this purpose, it was decided to introduce the wide dynamic range monitor technique that was developed in 2012 and has been in operation at the J-PARC beam transport line. The device is a two-dimensional beam profile monitor, and it has a dynamic range of approximately six digits of magnitude by using of Optical Transition Radiation and fluorescence screens. Eliminating harmful beam halos is the most important technique for high-intensity proton accelerators. Therefore, beam halo diagnosis is indispensable and becomes more and more important. New FNAL device has been manufactured in a collaboration between J-PARC and FNAL as a part of U.S.-Japan Science and Technology Cooperation Program in High Energy Physics. The equipment will be manufactured at J-PARC and will be shipped to FNAL in 2025.We designed the device to satisfy FNAL specifications: the beam energy, intensity, and size. Currently, most of the equipments are under construction. The large-aperture optical system has been completed and its optical characteristics are being evaluated at J-PARC. We have been also investigating measurement methods corresponding to FNAL bunch trains. This paper reports on the current status of these developments.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Physical Sciences Vistas: Perspectives on Simultaneous Excellence (Issue 1, 2023)

The issue begins with an article highlighting Physics Division’s involvement in diagnostic development that led to the measurement of ignition at the National Ignition Facility at Lawrence Livermore National Laboratory. Subsequent articles transition to some of the materials development occurring in Sigma, Materials Science and Technology, and Materials Physics and Applications divisions. This is inclusive of the development of next generation moderator materials as an enabling technology of small modular reactors. These materials will most likely be qualified at a facility at Idaho National Laboratory. The issue also highlights development of novel, additively manufactured foams for next generation weapons. This work is being done in close collaboration with the Kansas City National Security Campus to enable transition of materials development to production in a more agile way. Finally, an article describes Accelerator Operations and Technology Division’s hard work to replace the legacy remote instrumentation and control equipment at the Los Alamos Neutron Science Center (LANSCE) with a modern control system. The story discusses how that engineering success will lead to improved sustainability of the beam during operation and thus a better experience for all of our collaborators and partners in the LANSCE user program.

36 MATERIALS SCIENCE↗
NASA NTRS2019

An Approach for Uncertainty Quantification and Management of Unmanned Aerial Vehicle Health

The increasing interest in low-altitude unmanned aerial vehicle (UAV) operations is bringing along safety concerns. Performance of small, low-cost UAVs drastically changes with type, size and controller of the vehicle. Their reliability is lower when compared to reliability of commercial aircrafts, and the availability of on-board sensors for health and state awareness is extremely limited due to their size and propulsion capabilities. Uncertainty plays a dominant role in such a scenario, where a variety of UAVs of different size, propulsion systems, dynamic performance and reliability enters the low-altitude airspace. Unexpected failures could have dangerous consequences for both equipment and humans within that same airspace. As a result, a number of research works and methodologies are being proposed in the area of UAV dynamic modeling, health and safety monitoring, but uncertainty quantification is rarely addressed. Thus, this paper pro- poses a perspective towards uncertainty quantification for autonomous systems, giving special emphasis to a UAV health monitoring application. A formal approach to classify uncertainty is presented; it is utilized to identify the uncertainty sources in UAVs health and operations, and then map uncertainty within a predictive process. To show the application of the methodology proposed here, the design of a model-based powertrain health monitoring algorithm for small-size UAVs is used as case study. The example illustrates how the uncertainty quantification approach can help the modeling strategy, as well as the assessment of diagnostic and prognostic performance.

Health Monitoring↗
DOE OSTI2022

What We Learned From Analyzing 18 Million Rows of Commercial Buildings’ HVAC Fault Data

To achieve ambitious decarbonization goals it is critical that buildings operate to their full potential. Commercial HVAC systems, however, experience a wide range of operational faults, adversely affecting energy consumption, occupant comfort, and maintenance costs. Analytical tools such as fault detection & diagnostics (FDD) software identify and help diagnose these types of sensing, mechanical, or control-related faults. While significant energy savings has been documented for FDD, along with limited-scale studies on technical capabilities, there is a lack of empirical data on faults being reported by FDD tools. With FDD deployment accelerating significantly over the past decade there is an opportunity to gather and analyze data on commercial HVAC operational problems at an unprecedented scale. Such data could address many questions such as: [a] What faults are most commonly reported?; and [b] How does fault reporting vary by time of year and other possible drivers? A recent study into FDD fault reporting amassed the largest U.S. dataset of commercial HVAC air-side fault records, drawn from multi-year monitoring across over 60,000 pieces of HVAC equipment. The results of this study provide granular data on fault reporting for over 90 unique fault types. In this paper we provide an overview of the research process and highlight key findings and lessons learned. This study presents an extraordinary level of detail on FDD fault reporting characteristics across many climate zones and building types. Armed with these new insights, commercial building industry stakeholders can make better informed decisions when designing, configuring, and operating commercial HVAC systems.

Crowe, Eliot↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
NASA NTRS2002

Fusion for Space Propulsion

The need for fusion propulsion for interplanetary flights is discussed. For a propulsion system, there are three important system attributes: (1) The absolute amount of energy available, (2) the propellant exhaust velocity, and (3) the jet power per unit mass of the propulsion system (specific power). For efficient and affordable human exploration of the solar system, propellant exhaust velocity in excess of 100 km/s and specific power in excess of 10 kW/kg are required. Chemical combustion obviously cannot meet the requirement in propellant exhaust velocity. Nuclear fission processes typically result in producing energy in the form of heat that needs to be manipulated at temperatures limited by materials to about 2,800 K. Using the fission energy to heat a low atomic weight propellant produces propellant velocity of the order of 10 kinds. Alternatively the fission energy can be converted into electricity that is used to accelerate particles to high exhaust velocity. However, the necessary power conversion and conditioning equipment greatly increases the mass of the propulsion system. Fundamental considerations in waste heat rejection and power conditioning in a fission electric propulsion system place a limit on its jet specific power to the order of about 0.2 kW/kg. If fusion can be developed for propulsion, it appears to have the best of all worlds - it can provide the largest absolute amount of energy, the propellant exhaust velocity (> 100 km/s), and the high specific jet power (> 10 kW/kg). An intermediate step towards fusion propulsion might be a bimodal system in which a fission reactor is used to provide some of the energy to drive a fusion propulsion unit. There are similarities as well as differences between applying fusion to propulsion and to terrestrial electrical power generation. The similarities are the underlying plasma and fusion physics, the enabling component technologies, the computational and the diagnostics capabilities. These physics and engineering capabilities have been demonstrated for a fusion reactor gain (Q) of the order of unity (TFTR: 0.25, JET: 0.65, JT-60: Q(sub eq) approx. 1.25). These technological advances made it compelling for considering fusion for propulsion.

Thio, Y. C. Francis↗
NASA NTRS2005

Evaluation of shoulder integrity in space: first report of musculoskeletal US on the International Space Station

Investigative procedures were approved by Henry Ford Human Investigation Committee and NASA Johnson Space Center Committee for Protection of Human Subjects. Informed consent was obtained. Authors evaluated ability of nonphysician crewmember to obtain diagnostic-quality musculoskeletal ultrasonographic (US) data of the shoulder by following a just-in-time training algorithm and using real-time remote guidance aboard the International Space Station (ISS). ISS Expedition-9 crewmembers attended a 2.5-hour didactic and hands-on US training session 4 months before launch. Aboard the ISS, they completed a 1-hour computer-based Onboard Proficiency Enhancement program 7 days before examination. Crewmembers did not receive specific training in shoulder anatomy or shoulder US techniques. Evaluation of astronaut shoulder integrity was done by using a Human Research Facility US system. Crew used special positioning techniques for subject and operator to facilitate US in microgravity environment. Common anatomic reference points aided initial probe placement. Real-time US video of shoulder was transmitted to remote experienced sonologists in Telescience Center at Johnson Space Center. Probe manipulation and equipment adjustments were guided with verbal commands from remote sonologists to astronaut operators to complete rotator cuff evaluation. Comprehensive US of crewmember's shoulder included transverse and longitudinal images of biceps and supraspinatus tendons and articular cartilage surface. Total examination time required to guide astronaut operator to acquire necessary images was approximately 15 minutes. Multiple arm and probe positions were used to acquire dynamic video images that were of excellent quality to allow evaluation of shoulder integrity. Postsession download and analysis of high-fidelity US images collected onboard demonstrated additional anatomic detail that could be used to exclude subtle injury. Musculoskeletal US can be performed in space by minimally trained operators by using remote guidance. This technique can be used to evaluate shoulder integrity in symptomatic crewmembers after strenuous extravehicular activities or to monitor microgravity-associated changes in musculoskeletal anatomy. Just-in-time training, combined with remote experienced physician guidance, may provide a useful approach to complex medical tasks performed by nonexperienced personnel in a variety of remote settings, including current and future space programs. (c) RSNA, 2004.

Space Flight/education↗
DOE OSTI2023

Physics-informed Data-driven Degradation and Prognostic For Hydropower System

The hydropower system is a cyber-physical system, and the industry is experiencing high operation and maintenance (O&M) costs along with increasing unplanned outages, primarily due to aging equipment and new asset loading patterns. Current (O&M) practices in asset management are predominantly reactive rather than predictive and systematic. To address these challenges, a proposed physics-informed data-driven degradation model aims to simulate the health of components in various environments. Its purpose is to accurately characterize wear and fatigue in the pilot components of hydropower systems. Additionally, the model provides informed confidence in prognostic predictions concerning asset degradation and remaining life.

13 HYDRO ENERGY↗
NASA NTRS2000

Emission Line Spectra from Low-Density Laboratory Plasmas

Using spectroscopic equipment optimized for laboratory astrophysics, we are performing systematic measurements of the line emission from astrophysically relevant ions in the wavelength band between 1 and 400 Angstroms important to X-ray missions such as Chandra, XMM, Astro-E, and EUVE. Obtained in a controlled laboratory setting at electron densities similar to those found in stellar coronae, the data are used to test spectral modeling codes for accuracy and completeness. Our effort includes the compilation of the iron L-shell emission lines from 6-18 Angstroms and the iron M-shell emission lines from 50-200 Angstroms. Many lines have been identified for the first time, and the fluxes from lines missing in the spectral modeling codes are assessed. Our measurements also assess the accuracy of line excitation calculations, including direct electron-impact excitation, dielectronic recombination, and resonance excitation. These measurements yield a calibration of specific diagnostic line ratios. Examples of our current measurements are given.

Beiersdorfer, P.↗
NASA NTRS1998

High Speed A/D DSP Interface for Carrier Doppler Tracking

As on-board satellite systems continue to increase in ability to perform self diagnostic checks, it will become more important for satellites to initiate ground communications contact. Currently, the NASA Space Network requires users to pre-arranged times for satellite communications links through the Tracking and Data Relay Satellite (TDRS). One of the challenges in implementing an on-demand access protocol into the Space Network, is the fact that a low Earth orbiting (LEO) satellite's communications will be subject to a doppler shift which is outside the capability of the NASA ground station to lock onto. In a prearranged system, the satellite's doppler is known a priori, and the ground station is able to lock onto the satellite's signal. This paper describes the development of a high speed analog to digital interface into a Digital Signal Processor (DSP). This system will be used for identifying the doppler shift of a LEO satellite through the Space Network, and aiding the ground station equipment in locking onto the signal. Although this interface is specific to one application, it can be used as a basis for interfacing other devices with a DSP.

Baggett, Timothy↗
NASA NTRS2014

NASA Laboratory Analysis for Manned Exploration Missions

The Exploration Laboratory Analysis (ELA) project supports the Exploration Medical Capability Element under the NASA Human Research Program. ELA instrumentation is identified as an essential capability for future exploration missions to diagnose and treat evidence-based medical conditions. However, mission architecture limits the medical equipment, consumables, and procedures that will be available to treat medical conditions during human exploration missions. Allocated resources such as mass, power, volume, and crew time must be used efficiently to optimize the delivery of in-flight medical care. Although commercial instruments can provide the blood and urine based measurements required for exploration missions, these commercial-off-the-shelf devices are prohibitive for deployment in the space environment. The objective of the ELA project is to close the technology gap of current minimally invasive laboratory capabilities and analytical measurements in a manner that the mission architecture constraints impose on exploration missions. Besides micro gravity and radiation tolerances, other principal issues that generally fail to meet NASA requirements include excessive mass, volume, power and consumables, and nominal reagent shelf-life. Though manned exploration missions will not occur for nearly a decade, NASA has already taken strides towards meeting the development of ELA medical diagnostics by developing mission requirements and concepts of operations that are coupled with strategic investments and partnerships towards meeting these challenges. This paper focuses on the remote environment, its challenges, biomedical diagnostics requirements and candidate technologies that may lead to successful blood-urine chemistry and biomolecular measurements in future space exploration missions.

Laboratory Analysis↗
NASA NTRS2014

NASA Laboratory Analysis for Manned Exploration Missions

The Exploration Laboratory Analysis (ELA) project supports the Exploration Medical Capability Element under the NASA Human Research Program. ELA instrumentation is identified as an essential capability for future exploration missions to diagnose and treat evidence-based medical conditions. However, mission architecture limits the medical equipment, consumables, and procedures that will be available to treat medical conditions during human exploration missions. Allocated resources such as mass, power, volume, and crew time must be used efficiently to optimize the delivery of in-flight medical care. Although commercial instruments can provide the blood and urine based measurements required for exploration missions, these commercial-off-the-shelf devices are prohibitive for deployment in the space environment. The objective of the ELA project is to close the technology gap of current minimally invasive laboratory capabilities and analytical measurements in a manner that the mission architecture constraints impose on exploration missions. Besides micro gravity and radiation tolerances, other principal issues that generally fail to meet NASA requirements include excessive mass, volume, power and consumables, and nominal reagent shelf-life. Though manned exploration missions will not occur for nearly a decade, NASA has already taken strides towards meeting the development of ELA medical diagnostics by developing mission requirements and concepts of operations that are coupled with strategic investments and partnerships towards meeting these challenges. This paper focuses on the remote environment, its challenges, biomedical diagnostics requirements and candidate technologies that may lead to successful blood/urine chemistry and biomolecular measurements in future space exploration missions. SUMMARY The NASA Exploration Laboratory Analysis project seeks to develop capability to diagnose anticipated space exploration medical conditions on future manned missions. To achieve this goal, NASA will leverage existing point-of-care technology to provide clinical laboratory measurements in space. This approach will place the project on a path to minimize sample, reagent consumption, mass, volume and power. For successful use in the space environment, NASA specific conditions such as micro gravity and radiation, for example, will also need to be addressed.

Exploration Medical Capability↗