Results for “contingency control” — Page 19

NASA NTRS2001

Trajectory Design and Control for the Compton Gamma Ray Observatory Re-Entry

The Compton Gamma Ray Observatory (CGRO) controlled re-entry operation was successfully conducted in June of 2000. The surviving parts of the spacecraft landed in the Pacific Ocean within the nominal impact target zone. The design of the maneuvers to control the trajectory to accomplish this re-entry presented several challenges. These challenges included the timing and duration of the maneuvers, propellant management, post-maneuver state determination, collision avoidance with other spacecraft, accounting for the break-up of the spacecraft into several pieces with a wide range of ballistic coefficients, and ensuring that the impact footprint would remain within the desired impact target zone in the event of contingencies. This paper presents the initial re-entry trajectory design and traces the evolution of that design into the maneuver sequence used for the re-entry. The paper also discusses the spacecraft systems and operational constraints imposed on the trajectory design and the required modifications to the initial design based on those constraints. Data from the reentry operation are also presented.

Hoge, Susan↗

NASA NTRS1980

Orbiter electrical equipment utilization baseline

The baseline for utilization of Orbiter electrical equipment in both electrical and Environmental Control and Life Support System (ECLSS) thermal analyses is established. It is a composite catalog of Space Shuttle equipment, as defined in the Shuttle Operational Data Book. The major functions and expected usage of each component type are described. Functional descriptions are designed to provide a fundamental understanding of the Orbiter electrical equipment, to insure correlation of equipment usage within nominal analyses, and to aid analysts in the formulation of off-nominal, contingency analyses.

Source record↗

NASA NTRS1996

Application of Hybrid Optimization-Expert System for Optimal Power Management on Board Space Power Station

The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10 minutes. The models have been extensively tested using a case study for the Space Station Freedom and the results for the case study will be presented. Several future enhancements of the pre-scheduler and the 'rescheduler' have been outlined which include graphic analyzer for the on-line module, incorporating probabilistic considerations, including spatial location of the loads and the connectivity using a direct current (DC) load flow model.

Momoh, James↗

NASA NTRS2006

Control of Technology Transfer at JPL

Controlled Technology: 1) Design: preliminary or critical design data, schematics, technical flow charts, SNV code/diagnostics, logic flow diagrams, wirelist, ICDs, detailed specifications or requirements. 2) Development: constraints, computations, configurations, technical analyses, acceptance criteria, anomaly resolution, detailed test plans, detailed technical proposals. 3) Production: process or how-to: assemble, operated, repair, maintain, modify. 4) Manufacturing: technical instructions, specific parts, specific materials, specific qualities, specific processes, specific flow. 5) Operations: how-to operate, contingency or standard operating plans, Ops handbooks. 6) Repair: repair instructions, troubleshooting schemes, detailed schematics. 7) Test: specific procedures, data, analysis, detailed test plan and retest plans, detailed anomaly resolutions, detailed failure causes and corrective actions, troubleshooting, trended test data, flight readiness data. 8) Maintenance: maintenance schedules and plans, methods for regular upkeep, overhaul instructions. 9) Modification: modification instructions, upgrades kit parts, including software

Jet Propulsion Laboratory (JPL)↗

NASA NTRS1992

Verifying command sequences for satellite systems

We present a formal basis for the design of a Checker used in validating safe schedules and in selecting error recovery schedules for satellite control systems. This design includes a high-level specification of Checker behavior and properties (called flight rules) of safe schedules. Specifications are written in Timed Linear Logic (TLL). Validation of schedules is performed in terms of real-time telemetry and deduction system proof rules. Telemetry (state information for satellite subsystems) serves as input to the Checker. Detection of violation of a flight rule by the Checker results in the selection of a contingency plan (error recovery schedule). The Checker is illustrated in terms of the TOPEX/Poseidon Oceanographic Satellite System.

Peters, James F., III↗

NASA NTRS2009

Crew Exploration Vehicle (CEV) Potable Water System Verification Description

The Crew Exploration Vehicle (CEV), also known as Orion, will ferry a crew of up to six astronauts to the International Space Station (ISS), or a crew of up to four astronauts to the moon. The first launch of CEV is scheduled for approximately 2014. A stored water system on the CEV will supply the crew with potable water for various purposes: drinking and food rehydration, hygiene, medical needs, sublimation, and various contingency situations. The current baseline biocide for the stored water system is ionic silver, similar in composition to the biocide used to maintain quality of the water transferred from the Orbiter to the ISS and stored in Contingency Water Containers (CWCs). In the CEV water system, the ionic silver biocide is expected to be depleted from solution due to ionic silver plating onto the surfaces of the materials within the CEV water system, thus negating its effectiveness as a biocide. Since the biocide depletion is expected to occur within a short amount of time after loading the water into the CEV water tanks at the Kennedy Space Center (KSC), an additional microbial control is a 0.1 micron point of use filter that will be used at the outlet of the Potable Water Dispenser (PWD). Because this may be the first time NASA is considering a stored water system for longterm missions that does not maintain a residual biocide, a team of experts in materials compatibility, biofilms and point of use filters, surface treatment and coatings, and biocides has been created to pinpoint concerns and perform testing to help alleviate those concerns related to the CEV water system. Results from the test plans laid out in the paper presented to SAE last year (Crew Exploration Vehicle (CEV) Potable Water System Verification Coordination, 2008012083) will be detailed in this paper. Additionally, recommendations for the CEV verification will be described for risk mitigation in meeting the physicochemical and microbiological requirements on the CEV PWS.

Peterson, Laurie↗

DOE OSTI2025

Electric Grid Simulator For Human Factor Research

The developed code simulates real-time monitor and control for west area of IEEE 118-bus system. The 24-hour load profile for each bus is derived by scaling the system’s rated load in the PSSE sav file according to the California Independent System Operator’s Day-ahead load forecast for May 1, 2024. This simulator performs several critical functions: (1) Calculating time-series power flow every 4 seconds; (2) Updating and dispatching AGC signals every minute; (3) Conducting N-1 contingency analysis every 5 minutes. Additionally, the simulator can trip lines and subsequently update and dispatch AGC signals, running power flow analysis after each tripping event.

Huang, Jianqiao [Idaho National Laboratory (INL), ↗

NASA NTRSDate not supplied

Risk Assessment of Obstacle Collision for UAVs under off-nominal conditions

Enabling operations of unmanned aerial vehicles (UAVs) in low-altitude airspace, demands the need of robust risk monitoring framework for assessing the safety of airspace, ground-structures and people. As widespread applications emerge, the need of risk assessment becomes increasingly important for UAV flights beyond visual line-of-sight, especially subjected to off-nominal conditions introduced by component failures, degraded controllability or environmental disturbances such as wind gusts in an urban canyon. From a safety perspective, collision with obstacles can be detrimental not only to the vehicle and payload, but also to the structure and people on ground. Although it is safe to assume that approved UAVs would be equipped with collision avoidance systems, risk of collision which can be predicted for a flight trajectory even before the UAV encounters any obstacle is beneficial to resolve contingencies in its decision-making under off-nominal conditions. In this paper, a framework is presented for computing the risk of collision with obstacle based on a UAV's predicted trajectory, proximity to static and dynamic obstacles, sub-system state-of-health and external wind conditions. The conditional probability of trajectory deviation is generated using a Bayesian Belief Network (BBN) based on on-board sensor measurements. Further, a kinematic 3-DOF model is implemented to compute deviation in UAV's trajectory subjected to one case study of off-nominal condition i.e. wind gusts. Finally, the integrated risk factor is demonstrated on real data from experimental flights of an octocopter at NASA Langley Research Center, in presence of simulated obstacles and wind conditions. The proposed approach would enable risk-informed decision making process for timely mitigation of current and future unsafe events.

Portia Banerjee↗

NASA NTRSDate not supplied

Risk Assessment of Obstacle Collision for UAVs under Off-nominal Conditions

Enabling operations of unmanned aerial vehicles (UAVs) in low-altitude airspace demands the need of robust risk monitoring framework for assessing the safety of airspace, ground structures and people. As widespread applications emerge, the need of risk assessment becomes increasingly important for UAV flights beyond visual line-of-sight, especially subjected to off-nominal conditions introduced by component failures, degraded controllability or environmental disturbances such as wind gusts in an urban canyon. From a safety perspective, collision with obstacles can be detrimental not only to the vehicle and payload, but also to the structure and people on ground. Although it is safe to assume that approved UAVs would be equipped with collision avoidance systems, risk of collision which can be predicted for a flight trajectory even before the UAV encounters any obstacle is beneficial to resolve contingencies in its decision-making under off-nominal conditions. In this paper, a framework is presented for computing the risk of collision with obstacle based on a UAV’s predicted trajectory, proximity to static and dynamic obstacles, sub-system state-of-health and external wind conditions. The conditional probability of trajectory deviation is generated using a Bayesian Belief Network (BBN) based on on-board sensor measurements. Further, a kinematic 3-DOF model is implemented to compute deviation in UAV’s trajectory subjected to one case study of off-nominal condition i.e. wind gusts. Finally, the integrated risk factor is demonstrated on real data from experimental flights of an octocopter at NASA Langley Research Center, in presence of simulated obstacles and wind conditions. The proposed approach would enable risk-informed decision making process for timely mitigation of current and future unsafe events.

Bayesian network↗

NASA NTRSDate not supplied

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↗

NASA NTRS2024

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↗

NASA NTRSDate not supplied

HAT m:N Activity Overview

Since 2020, researchers from the Human Autonomy Teaming (HAT) Laboratory at NASA Ames Research Center have conducted human-in-the-loop (HITL) simulation research to study a new control paradigm for operations involving multiple remotely piloted aircraft systems (RPAS). Colloquially referred to as "m:N," this paradigm is characterized by multiple operators collaboratively controlling multiple vehicles between them. The m:N name expresses a ratio whereby m is the number of operators and N is the number of vehicles shared between them. In this presentation, HAT Lab researchers provide a high-level overview of the m:N studies that have been performed to-date. These include a study of the m:N concept of operations (CONOPS) and the attending roles and responsibilities ("ConOps/R&R Sim"), a study focused on contingency management involving dynamic, inter-operator transfers of vehicles ("Handoff Sim"), and a study examining the effects of pilot-ATC communication systems on workload ("UAM Comms Sim"). A selection of key results are provided. The presentation concludes with a brief discussion of planned research into m:N operations.

m:N↗

NASA NTRS1999

TRMM On Orbit Attitude Control System Performance

This paper presents an overview of the Tropical Rainfall Measuring Mission (TRMM) Attitude Control System (ACS) along with detailed in-flight performance results for each operational mode. The TRMM spacecraft is an Earth-pointed, zero momentum bias satellite launched on November 27, 1997 from Tanegashima Space Center, Japan. TRMM is a joint mission between NASA and the National Space Development Agency (NASDA) of Japan designed to monitor and study tropical rainfall and the associated release of energy. Launched to provide a validation for poorly known rainfall data sets generated by global climate models, TRMM has demonstrated its utility by reducing uncertainties in global rainfall measurements by a factor of two. The ACS is comprised of Attitude Control Electronics (ACE), an Earth Sensor Assembly (ESA), Digital Sun Sensors (DSS), Inertial Reference Units (IRU), Three Axis Magnetometers (TAM), Coarse Sun Sensors (CSS), Magnetic Torquer Bars (MTB), Reaction Wheel Assemblies (RWA), Engine Valve Drivers (EVD) and thrusters. While in Mission Mode, the ESA provides roll and pitch axis attitude error measurements and the DSS provide yaw updates twice per orbit. In addition, the TAM in combination with the IRU and DSS can be used to provide pointing in a contingency attitude determination mode which does not rely on the ESA. Although the ACS performance to date has been highly successful, lessons were learned during checkout and initial on-orbit operation. This paper describes the design, on-orbit checkout, performance and lessons learned for the TRMM ACS.

Robertson, Brent↗

DOE OSTI2025

Grid Resiliency using Hydro-based Microgrids During Wildfires

The primary objective of this project is to assess the techno-economic viability of hydropower resources with supplementary investments, including microgrid controllers, storage solutions, load banks, additional generation like diesel generators, communication links, and transmission infrastructure. The aim is to enable these systems to operate autonomously (in islanded mode) and ensure grid resiliency during and after wildfire events. The project seeks to establish a comprehensive framework for setting up hydropower-based microgrids, from risk estimation to final investment decisions. These microgrids can provide critical support during emergencies and offer additional grid stability and revenue opportunities during regular operations and other system contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Impact of Wide-Area Oscillation Damping Control using Measurement-Driven Approach on System Separation - Saudi Grid Case Study

In any interconnected power grid, low-frequency oscillations is a major problem that can limit the power transfer capability and deteriorate power system security due to potential low-damped or even undamped oscillations. Synchronized measurements provided by PMUs enable the design and development of wide-area oscillation damping controllers (WADC) based on measurement-driven model to overcome the limitations of traditional controllers. This work focuses on the impact of a W ADC based on a measurement-driven approach on system separation for the Saudi Electricity Company (SEC) grid. A grid model is provided by SEC for this study. Modal analysis is performed to identify the oscillation mode of interest for which the controller is designed. Damping the dominant oscillation mode helps slightly to improve transient stability of the system. Considering bus frequency at different locations in SEC's system as the candidate observation signals, the optimal observation signal is chosen for the W ADC by using the FFT method. The system transfer function model is constructed by utilizing probing measurements. Then, the W ADC parameters are calculated based on the identified model. The performance of the designed W ADC is tested under different contingencies.

Altarjami, Ibrahim↗

NASA NTRS1991

Measurement and modification of the EEG and related behavior

Electrophysiological changes in the sensorimotor pathways were found to accompany the effect of rhythmic EEG patterns in the sensorimotor cortex. Additionally, several striking behavioral changes were seen, including in particular an enhancement of sleep and an elevation of seizure threshold to epileptogenic agents. This raised the possibility that human seizure disorders might be influenced therapeutically by similar training. Our objective in human EEG feedback training became not only the facilitation of normal rhythmic patterns, but also the suppression of abnormal activity, thus requiring complex contingencies directed to the normalization of the sensorimotor EEG. To achieve this, a multicomponent frequency analysis was developed to extract and separate normal and abnormal elements of the EEG signal. Each of these elements was transduced to a specific component of a visual display system, and these were combined through logic circuits to present the subject with a symbolic display. Variable criteria provided for the gradual shaping of EEG elements towards the desired normal pattern. Some 50-70% of patients with poorly controlled seizure disorders experienced therapeutic benefits from this approach in our laboratory, and subsequently in many others. A more recent application of this approach to the modification of human brain function in our lab has been directed to the dichotomous problems of task overload and underload in the contemporary aviation environment. At least 70% of all aviation accidents have been attributed to the impact of these kinds of problems on crew performance. The use of EEG in this context has required many technical innovations and the application of the latest advances in EEG signal analysis. Our first goal has been the identification of relevant EEG characteristics. Additionally, we have developed a portable recording and analysis system for application in this context. Findings from laboratory and in-flight studies suggest that we will be able to detect appropriate changes in brain function, and feed this information to on-board computers for modification of mission requirements and/or crew status.

Sterman, M. B.↗

NASA NTRS1994

Microgravity Flight - Accommodating Non-Human Primates

Spacelab Life Sciences-3 (SLS-3) was scheduled to be the first United States man-tended microgravity flight containing Rhesus monkeys. The goal of this flight as in the five untended Russian COSMOS Bion flights and an earlier American Biosatellite flight, was to understand the biomedical and biological effects of a microgravity environment using the non-human primate as human surrogate. The SLS-3/Rhesus Project and COSMOS Primate-BIOS flights all utilized the rhesus monkey Macaca mulatta. The ultimate objective of all flights with an animal surrogate has been to evaluate and understand biological mechanisms at both the system and cellular level, thus enabling rational effective countermeasures for future long duration human activity under microgravity conditions and enabling technical application to correction of common human physiological problems within earth's gravity, e.g., muscle strength and reloading, osteoporosis, immune deficiency diseases. Hardware developed for the SLS-3/Rhesus Project was the result of a joint effort with the French Centre National d'Etudes Spatiales (CNES) and the United States National Aeronautics and Space Administration (NASA) extending over the last decade. The flight hardware design and development required implementation of sufficient automation to insure flight crew and animal bio-isolation and maintenance with minimal impact to crew activities. A variety of hardware of varying functional capabilities was developed to support the scientific objectives of the original 22 combined French and American experiments, along with 5 Russian co-investigations, including musculoskeletal, metabolic, and behavioral studies. Unique elements of the Rhesus Research Facility (RRF) included separation of waste for daily delivery of urine and fecal samples for metabolic studies and a psychomotor test system for behavioral studies along with monitored food measurement. As in untended flights, telemetry measurements would allow monitoring of thermoregulation, muscular, and cardiac responses to weightlessness. In contrast, the five completed Cosmos/Bion flights, lacked the metabolic samples and behavioral task monitoring, but did facilitate studies of the neurovestibular system during several of the flights. The RRF accommodated two adult 8-11 kg rhesus monkeys, while the Russian experiments and hardware were configured for a younger animal in the 44 kg range. Both the American and Russian hardware maintained a controlled environmental system, specifically temperature, humidity, a timed lighting cycle, and had means for providing food and fluids to the animal(s). Crew availability during a Shuttle mission was to be an optimal condition for retrieval and refrigeration of the animal urine samples along with a manual calcein injection which could lead to greater understanding of bone calcium incorporation. A special portable bioisolation glove box was under development to support this aspect of the experiment profile along with the capability of any contingency human intervention. As a result of recent U.S./Russian negotiations, funding for Space Station, and a series of other events, the SLS-3 mission was cancelled and applicable Rhesus Project experiments incorporated into the Russian Bion 11 and 12 missions. A presentation of the RRF and COSMOS/Bion rhesus hardware is presented along with current plans for the hardware.

Dalton, Bonnie P.↗

NASA NTRS1995

Microgravity Flight: Accommodating Non-Human Primates

Spacelab Life Sciences-3 (SLS-3) was scheduled to be the first United States man-tended microgravity flight containing Rhesus monkeys. The goal of this flight as in the five untended Russian COSMOS Bion flights and an earlier American Biosatellite flight, was to understand the biomedical and biological effects of a microgravity environment using the non-human primate as human surrogate. The SLS-3/Rhesus Project and COSMOS Primate-BIOS flights all utilized the rhesus monkey, Macaca mulatta. The ultimate objective of all flights with an animal surrogate has been to evaluate and understand biological mechanisms at both the system and cellular level, thus enabling rational effective countermeasures for future long duration human activity under microgravity conditions and enabling technical application to correction of common human physiological problems within earth's gravity, e.g., muscle strength and reloading, osteoporosis, immune deficiency diseases. Hardware developed for the SLS-3/Rhesus Project was the result of a joint effort with the French Centre National d'Etudes Spatiales (CNES) and the United States National Aeronautics and Space Administration (NASA) extending over the last decade. The flight hardware design and development required implementation of sufficient automation to insure flight crew and animal bio-isolation and maintenance with minimal impact to crew activities. A variety of hardware of varying functional capabilities was developed to support the scientific objectives of the original 22 combined French and American experiments, along with 5 Russian co-investigations, including musculoskeletal, metabolic, and behavioral studies. Unique elements of the Rhesus Research Facility (RRF) included separation of waste for daily delivery of urine and fecal samples for metabolic studies and a psychomotor test system for behavioral studies along with monitored food measurement. As in untended flights, telemetry measurements would allow monitoring of thermoregulation, muscular, and cardiac responses to weightlessness. In contrast, the five completed Cosmos/Bion flights, lacked the metabolic samples and behavioral task monitoring, but did facilitate studies of the neurovestibular system during several of the flights. The RRF accommodated two adult 8-11 kg rhesus monkeys, while the Russian experiments and hardware were configured for a younger animal in the 44 kg range. Both the American and Russian hardware maintained a controlled environmental system, specifically temperature, humidity, a timed lighting cycle, and had means for providing food and fluids to the animal(s). Crew availability during a Shuttle mission was to be an optimal condition for retrieval and refrigeration of the animal urine samples along with a manual calcein injection which could lead to greater understanding of bone calcium incorporation. A special portable bioisolation glove box was under development to support this aspect of the experiment profile along with the capability of any contingency human intervention. As a result of recent U.S./Russian negotiations, funding for Space Station, and a series of other events, the SLS-3 mission was cancelled and applicable Rhesus Project experiments incorporated into the Russian Bion 11 and 12 missions. A presentation of the RRF and COSMOS/Bion rhesus hardware is presented along with current plans for the hardware.

Dalton, Bonnie P.↗