A novel contingency screening and ranking index for grid-forming converter-based sources following generator outage
Not Available
24 POWER TRANSMISSION AND DISTRIBUTION↗
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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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Novel Data-Driven Distributed Learning Framework for Solving AC Power Flow for Large Interconnected Systems
Not Available
42 ENGINEERING↗
OSIRIS-REx Screening Experience & Lessons Learned
On September 24, 2023, the NASA OSIRIS-REx spacecraft returned a sample of asteroid Bennu, approaching on a hyperbolic impact trajectory relative to Earth. At approximately 108,000 km altitude and four hours prior to hitting the top of the atmosphere, the Sample Return Capsule (SRC) separated from the spacecraft bus, targeting the Utah Test and Training Range. Twenty minutes later, the bus performed a large divert maneuver to fly by at a perigee altitude of ~780 km. Given the immense scientific value of the sample, substantial efforts were undertaken by NASA CARA and the OSIRIS-REx mission to ensure safe passage of the objects from GEO through LEO. This presentation provides an overview of collision avoidance maneuver (CAM) options, results of screenings, coordination with DoD for contingency observations, and lessons learned for screening future Earth flyby and entry trajectories. Two particular challenges included screening two objects using a much larger than normal 250 km spherical monitor volume and decision planning for a single CAM while the SRC was still attached that would alter both trajectories. The larger, non-standard screening volume resulted in custom procedures that CARA personnel had to run manually for each screening, and the initial long propagation times while the objects were more than a week out required significant computing resources. With a single CAM opportunity at 13 hours out, the decision to execute a maneuver had to consider the risk to both objects, where one could imagine a situation where the maneuver would clear a high-risk conjunction for one object and introduce one for the other – begging the question of relative risk posture between the SRC and bus. These among other unique aspects of Earth flyby and entry missions led to novel planning and implementation procedures to support future missions of this type.
Dolan E. Highsmith↗
Alternating Direction Decomposition with Strong Bounding and Convexification (ADDSBC) for Solving Security Constrained AC Unit Commitment Problems
This project aims to develop efficient and robust computational methods for solving the security-constrained unit commitment and alternating current optimal power flow problem (SC-UC-ACOPF). The SC-UC-ACOPF problem is at the center of the short-term operation of the U.S. Power Grid. It is solved every week, every day, and every 10 minutes to plan for the optimal action of electricity generation and consumption by minimizing the generation cost and maintaining power system reliability against potential disruptions of equipment failures. In mathematical terms, SC-UC-ACOPF is a challenging large-scale mixed-integer nonlinear optimization model. This means that the decisions involve both discrete variables, e.g. the turning on and off of generators and switching of transmission lines and transformers, and continuous decisions, e.g. the amount of energy generated by each generator and the power flows in the power grid. The physics of the power flow is described by nonlinear equations involving real and reactive power and bus voltages. Another key feature is the large number of contingencies, i.e. the system needs to stay reliable in face of failure of any one equipment, such as transmission lines and generators. The U.S. power grids are extremely complicated and large scale with more than 5,000 generators, 50,000 buses, and 100,000 high-voltage transmission lines, making the SC-UC-ACOPF a very large-scale computation challenge. The research developed in this project aims to solve the SC-UC-ACOPF problems in the three timescales, i.e. weekly, daily, and every 10-min. The proposed computational methods are built on a principled algorithmic approach of decomposition and penalization. More specifically, the algorithm develops spatial and temporal decomposition by exploiting the strong temporal coupling and weak spatial coupling of the UC problem and the complementary feature, i.e. weak temporal coupling and strong spatial coupling of the ACOPF problem. The algorithm also leverages recent progresses in strong convex relaxation of ACOPF. A unique feature of the proposed approach is that it generates a valid, global upper bound on the optimal maximum profit. In this way, a global optimality gap is available to measure the quality of the solution. To further speed up computation, the research team has developed a plethora of effective heuristics to strengthen the iterative penalty-based decomposition framework. For instance, a heuristic is developed to construct inner approximations of the time coupling constraints within the time decoupled problems. Contingencies are pre-screened and low-rank matrix computation is exploited to find the almost unique solution to each contingency. A novel heuristic for line switching is proposed and tested with positive impacts on instances where line switching is beneficial. Taking a systematic approach and carefully handling every detail of the problem pays off. The TIM-GO’s performance throughout the trials and the final event was stellar. TIM-GO garnered the second highest total prize money and is ranked in the top three positions across all categories of comparison.
97 MATHEMATICS AND COMPUTING↗
Computerized atmospheric trace contaminant control simulation for manned spacecraft
Buildup of atmospheric trace contaminants in enclosed volumes such as a spacecraft may lead to potentially serious health problems for the crew members. For this reason, active control methods must be implemented to minimize the concentration of atmospheric contaminants to levels that are considered safe for prolonged, continuous exposure. Designing hardware to accomplish this has traditionally required extensive testing to characterize and select appropriate control technologies. Data collected since the Apollo project can now be used in a computerized performance simulation to predict the performance and life of contamination control hardware to allow for initial technology screening, performance prediction, and operations and contingency studies to determine the most suitable hardware approach before specific design and testing activities begin. The program, written in FORTRAN 77, provides contaminant removal rate, total mass removed, and per pass efficiency for each control device for discrete time intervals. In addition, projected cabin concentration is provided. Input and output data are manipulated using commercial spreadsheet and data graphing software. These results can then be used in analyzing hardware design parameters such as sizing and flow rate, overall process performance and program economics. Test performance may also be predicted to aid test design.
Perry, J. L.↗
SRMS Assisted Docking and Undocking for the Orbiter Repair Maneuver
As part of the Orbiter Repair Maneuver (ORM) planned for Return to Flight (RTF) operations, the Shuttle Remote Manipulator System (SRMS) must undock the Orbiter, maneuver it through a complex trajectory at extremely low rates, present it to an EVA crewman at the end of the Space Station Remote Manipulator System to perform the Thermal Protection System (TPS) repair, and then retrace back through the trajectory to dock the Orbiter with the Orbiter Docking System (ODS). The initial and final segments of this operation involve the interaction between the SRMS, ISS, Orbiter and ODS. Previously, a technique entitled "SRMS assisted docking" for installation of a payload to the ODS had been developed and was utilized for the Russian provided Docking Module on STS-74 during Shuttle-Mir missions and both the Node 1 and FGB elements on STS-88/Flight 2A. This procedure consisted of the SRMS grappling the respective payload, maneuvering it to a pre-install position inches above the ODS Androgynous Peripheral Attachment System (APAS) ring, commanding the SRMS into Test mode (which allows brakes-off motion of the joints), and then down-firing Primary Reaction Control System (PRCS) jets in order to effect a capture of the APAS latches. Once a successful capture had been achieved, then the AP AS was operated through its nominal retraction sequence to complete the mating sequence. While this technique can once again be used for the tail end docking portion of the ORM, the initial undocking of the orbiter and ISS vehicles with the assistance of the SRMS has yet to be attempted on orbit. The objective here is to determine the most efficient means to separate or extract the vehicles. Two techniques were analyzed in support of RTF: (1) the 'nominal' demating from the mated interface, and (2) the SRMS performing the operation (either in an active or passive fashion). In the first operation, the demating process would replicate standard undocking operations, with the exception that the SRMS is allowed to arrest the resulting motion. The second operation would be to extend the APAS ring to a ready to dock position, open the capture latches, and then detach the vehicles using the SRMS either actively or passively. In the active case, the APAS ring is extended and latched, and the SRMS is commanded to pull the two interfaces apart (assuming that the effective pull force of the SRMS can overcome the spec values of the combined latch resistance). In the passive case, the SRMS brakes are engaged and the AP AS mechanism is commanded to retract, pulling the two interfaces apart. Since the emphasis of both STS-74 and STS-88 had solely been on the installation operation, as opposed to the separation operation, two new models required development and incorporation within simulation tools designed to analyze those scenarios. These enhancements included: (1) a detailed demating dynamics model to characterize the pusher spring characteristics during undocking, and (2) contact and mechanical system modeling of the back side of the latches to represent unlatching dynamics. This paper first provides an overview of the Monte-Carlo screening analysis for the installation (both nominal and contingency), including the variation of separation distance, misalignment conditions, SRMS joint/brake parameter characteristics, and PRCS jet combinations and corresponding thrust durations. The resulting 'optimum' solution is presented based on trade studies between predicted capture success and integrated system loads. This paper then discusses the upgrades to the APAS math model associated with the new SRMS assisted undocking technique and reviews simulation results for various options investigated for either the active and passive separation of the ISS from the Orbiter.
Space Station Remote Manipulator System↗
Heart Rhythm Monitoring in the Constellation Lunar and Launch/Landing EVA Suit: Recommendations from an Expert Panel
Currently there are several physiological monitoring requirements for Extravehicular Activity (EVA) in the Human-Systems Interface Requirements (HSIR) document, including continuous heart rhythm monitoring. However, it is not known whether heart rhythm monitoring in the lunar surface space suit is a necessary capability for lunar surface operations or in launch/landing suit the event of a cabin depressurization enroute to or from the moon. Methods: Current US astronaut corps demographic information was provided to an expert panel of cardiovascular medicine experts, including specialists in electrophysiology, exercise physiology, interventional cardiology and arrhythmia. This information included averages for male/female age, body mass index (BMI), blood pressure, cholesterol, inflammatory markers, echocardiogram, ranges for coronary artery calcium (CAC) scores for long duration astronauts, and ranges for heart rate (HR) and metabolic (MET) rates obtained during microgravity and lunar EVA. Results: The panel determined that no uncontrolled hazard was likely to occur in the suit during lunar surface or contingency microgravity ops that would require ECG monitoring in the highly screened US astronaut population. However having the capability for rhythm monitoring inside the vehicle (IVA) was considered critical to manage an astronaut in distress. Discussion: Heart rate (HR) monitoring alone allows effective monitoring of astronaut health and function. Consequently, electrocardiographic (ECG) monitoring capability as a clinical tool is not essential in the lunar or launch/landing space suit. However, the panel considered that rhythm monitoring could be useful in certain clinical situations, it was not considered required for safe operations. Also, lunar vehicles should be required to have ECG monitoring capability with a minimum of 5-lead ECG (derived 12- lead) for IVA medical assessments.
Scheuring, Richard A.↗
Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions
Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.
J Lemery↗
Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions
Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.
Medical Operations↗
Discrete Empirical Interpolation Method Based Dynamic Load Model Reduction
Dynamic load models add significant complexity to bulk power system time-domain simulations. The complexity is due to the large number of ordinary differential equations (ODEs) introduced by the dynamic load components such as induction motors. It is challenging to derive reduced-order models (ROMs) for dynamic loads due to the nonlinear functions in their governing equations. This paper applies the discrete empirical interpolation method enhanced proper orthogonal decomposition (DEIM-POD) to approximate the full dynamic load model with the ROM that minimizes the projection error of the nonlinear functions in dynamic load ODEs onto their dominant modes. This approach only requires evaluation of nonlinear functions at selected observation points. The observation points selected by DEIM also provide information for screening critical load buses where dynamic load model parameters contribute the most to the accuracy of ROM across multiple contingencies. The proposed approach is validated on IEEE 9-bus, WECC 179-bus and 2384-bus Polish systems.
bulk power system↗
An optimally tuned range-separated hybrid starting point for ab initio GW plus Bethe–Salpeter equation calculations of molecules
The ab initio GW plus Bethe–Salpeter equation (GW-BSE, where G is the one particle Green's function and W is the screened Coulomb interaction) approach has emerged as a leading method for predicting excitations in both solids and molecules with a predictive power contingent upon several factors. Among these factors are the (1) generalized Kohn–Sham eigensystem used to construct the GW self-energy and to solve the BSE and (2) the efficacy and suitability of the Tamm–Dancoff approximation. Here, we present a detailed benchmark study of low-lying singlet excitations from a generalized Kohn–Sham (gKS) starting point based on an optimally tuned range-separated hybrid (OTRSH) functional. We show that the use of this gKS starting point with one-shot G0W0 and G0W0-BSE leads to the lowest mean absolute errors (MAEs) and mean signed errors (MSEs), with respect to high-accuracy reference values, demonstrated in the literature thus far for the ionization potentials of the GW100 benchmark set and for low-lying neutral excitations of Thiel’s set molecules in the gas phase, without the need for self-consistency. The MSEs and MAEs of one-shot G0W0-BSE@OTRSH excitation energies are comparable to or lower than those obtained with other functional starting points after self-consistency. Additionally, we compare these results with linear-response time-dependent density functional theory (TDDFT) calculations and find GW-BSE to be superior to TDDFT when calculations are based on the same exchange-correlation functional. This work demonstrates tuned range-separated hybrids used in combination with GW and GW-BSE can greatly suppress starting point dependence for molecules, leading to accuracy similar to that for higher-order wavefunction-based theories for molecules without the need for costlier iterations to self-consistency.
McKeon, Caroline A. (ORCID:0000000217373503)↗
Real-Time Dose Prediction for Artemis Missions
As large solar energetic particle (SEP) events can add significant radiation dose to astronauts in a short period of time and even induce acute clinical responses during missions, they present a concern for manned space flight operation. To assist the operations team in modeling and monitoring organ doses and any possible acute radiation-induced risks to astronauts during SEP events in real time, ARRT (Acute Radiation Risks Tool) 1.0 has been developed and successfully tested for Artemis I mission. The ARRT 2.0 described in this work integrates an established SEP forecasting model – UMASEP-100, further enabling real-time dose prediction for the upcoming Artemis II and following missions. With the new module linking with UMASEP-100 outputs in real time, the total BFO doses of most significant events can be communicated at the time of onset and hours before the peak. This is based on a flux-dose formula identified from comparing UMASEP-100 results with transport calculation for the events during 1994-2013 and validated with events outside that period. ARRT 2.0 also shows capability to distinguish minor events from significant ones to screen false alarms that will cause disruptions for space activities. This improvement provides additional information for operational teams to make timely decisions in contingent scenarios of severe SEP events to mitigate radiation exposure.
S Hu↗
Real-Time Dose Prediction for Artemis Missions
As large solar energetic particle (SEP) events can add significant radiation dose to astronauts in a short period of time and even induce acute clinical responses during missions, they present a concern for manned space flight operation. To assist the operations team in modeling and monitoring organ doses and any possible acute radiation-induced risks to astronauts during SEP events in real time, ARRT (Acute Radiation Risks Tool) 1.0 has been developed and successfully tested for Artemis I mission. The ARRT 2.0 described in this work integrates an established SEP forecasting model – UMASEP-100, further enabling real-time dose prediction for the upcoming Artemis II and following missions. With the new module linking with UMASEP-100 outputs in real time, the total BFO doses of most significant events can be communicated at the time of onset and hours before the peak. This is based on a flux-dose formula identified from comparing UMASEP-100 results with transport calculation for the events during 1994-2013 and validated with events outside that period. ARRT 2.0 also shows capability to distinguish minor events from significant ones to screen false alarms that will cause disruptions for space activities. This improvement provides additional information for operational teams to make timely decisions in contingent scenarios of severe SEP events to mitigate radiation exposure.
Shaowen Hu↗
Study of space shuttle EVA/IVA support requirements. Volume 2: EVA/IVA tasks, guidelines, and constraints definition
The guidelines for EVA and IVA tasks to be performed on the space shuttle are defined. In deriving tasks, guidelines, and constraints, payloads were first identified from the mission model. Payload requirements, together with man and manipulator capabilities, vehicle characteristics and operation, and safety considerations led to a definition of candidate tasks. Guidelines and constraints were also established from these considerations. Scenarios were established, and screening criteria, such as commonality of EVA and IVA activities, were applied to derive representative planned and unplanned tasks. The whole spectrum of credible contingency situations with a potential requirement for EVA/IVA was analyzed.
Webbon, B. W.↗
Assessment of Near-Term Fuel Screening and Qualification Needs for Nuclear Thermal Propulsion Systems
Nuclear thermal propulsion (NTP) is an in-space propulsion technology capable of both high specific impulse (850–1000 s) and thrust (44–1112 kN), which can help reduce trip times for crewed missions beyond low Earth orbit. NTP technology has been demonstrated during historic programs. Over 20 ground test reactor experiments were performed, which demonstrated the prototypic reactor operations, during the Nuclear Engine for Rocket Vehicle Application (NERVA)/Rover program (1955–1972). Although historical programs have shown that NTP is a viable in-space propulsion technology, developing NTP in modern programs is contingent on the development and qualification of ultrahigh-temperature nuclear fuel technologies that can withstand engine operating conditions. In historical NTP development programs such as NERVA/Rover, prototypic reactor/engine schemes were ground tested to assess the overall system feasibility and to qualify the reactor fuel forms for eventual flight systems. Although this approach is effective to verify fuel performance under prototypic conditions, relying solely on full-scale NTP reactor tests as the pathway for verifying or qualifying fuel is inefficient and cost prohibitive today. Additionally, modern nuclear licensing requirements state that before test reactor approval, reactor components and fuel elements should be qualified via non-nuclear (out-of-pile) and nuclear (in-pile) testing under representative operating conditions. Using this methodology, fuel matures as production scale fabrication methods are established, and as produced fuel performance is demonstrated. Here, this paper provides an overview of historical approaches to NTP fuel performance maturation, including fuel screening and qualification needs, and provides insight for establishing an efficient testing paradigm that can be implemented to rapidly and affordably develop NTP fuel forms for eventual qualification.
42 ENGINEERING↗
Candidate Materials Evaluated for a High-Temperature Stirling Convertor Heater Head
The Department of Energy and NASA have identified Stirling Radioisotope Generators (SRGs) as a candidate power system for use on long-duration, deep-space science missions and Mars rovers. One of the developments planned for an upgraded version of the current SRG design is to achieve higher efficiency by increasing the overall operating temperature of the system. Currently, the SRG operates with a heater head temperature of 650 C and is fabricated from the nickel-base superalloy 718. The current operating temperature is at the limit of alloy 718 s capability, and any planned increase in temperature will be contingent on identifying a more capable material from which to fabricate the heater head. To this end, personnel at the NASA Glenn Research Center are evaluating advanced materials for a high-temperature heater head to allow a higher convertor temperature ratio and, thus, increase the system efficiency. A generic list of properties that were used to screen the candidate materials follows: (1) creep, (2) fabricability, (3) helium gas containment, (4) long-term stability and compatibility, (5) ability to form a hermetical closeout seal, and (6) ductility and toughness.
Bowman, Randy R.↗
Orientation illusions and heart-rate changes during short-radius centrifugation
Intermittent short-radius centrifugation is a promising countermeasure against the adverse effects of prolonged weightlessness. To assess the feasibility of this countermeasure, we need to understand the disturbing sensory effects that accompany some movements carried out during rotation. We tested 20 subjects who executed yaw and pitch head movements while rotating at constant angular velocity. They were supine with their main body axis perpendicular to earth gravity. The head was placed at the centrifuge's axis of rotation. Head movements produced a transient elevation of heart-rate. All observers reported head-contingent sensations of body tilt although their bodies remained supine. Mostly, the subjective sensations conform to a model based on semicircular canal responses to angular acceleration. However, some surprising deviations from the model were found. Also, large inter-individual differences in direction, magnitude, and quality of the illusory body tilt were observed. The results have implications for subject screening and prediction of subjective tolerance for centrifugation.
NASA Discipline Neuroscience↗
Heart Rhythm Monitoring in the Constellation Lunar and Launch/Landing EVA Suit: Recommendations from an Expert Panel
There are currently several physiological monitoring requirements for EVA in the Human-Systems Interface Requirements (HSIR) document. There are questions as to whether the capability to monitor heart rhythm in the lunar surface space suit is a necessary capability for lunar surface operations. Similarly, there are questions as to whether the capability to monitor heart rhythm during a cabin depressurization scenario in the launch/landing space suit is necessary. This presentation seeks to inform space medicine personnel of recommendations made by an expert panel of cardiovascular medicine specialists regarding in-suit ECG heart rhythm monitoring requirements during lunar surface operations. After a review of demographic information and clinical cases and panel discussion, the panel recommended that ECG monitoring capability as a clinical tool was not essential in the lunar space suit; ECG monitoring was not essential in the launch/landing space suit for contingency scenarios; the current hear rate monitoring capability requirement for both launch/landing and lunar space suits should be maintained; lunar vehicles should be required to have ECG monitoring capability with a minimum of 5-lead ECG for IVA medical assessments; and, exercise stress testing for astronaut selection and retention should be changed from the current 85% maximum heart rate limit to maximal, exhaustive 'symptom-limited' testing to maximize diagnostic utility as a screening tool for evaluating the functional capacity of astronauts and their cardiovascular health.
Scheuring, Richard A.↗