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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

The Integrated Medical Model - Optimizing In-flight Space Medical Systems to Reduce Crew Health Risk and Mission Impacts

The Integrated Medical Model (IMM) is a decision support tool used by medical system planners and designers as they prepare for exploration planning activities of the Constellation program (CxP). IMM provides an evidence-based approach to help optimize the allocation of in-flight medical resources for a specified level of risk within spacecraft operational constraints. Eighty medical conditions and associated resources are represented in IMM. Nine conditions are due to Space Adaptation Syndrome. The IMM helps answer fundamental medical mission planning questions such as What medical conditions can be expected? What type and quantity of medical resources are most likely to be used?", and "What is the probability of crew death or evacuation due to medical events?" For a specified mission and crew profile, the IMM effectively characterizes the sequence of events that could potentially occur should a medical condition happen. The mathematical relationships among mission and crew attributes, medical conditions and incidence data, in-flight medical resources, potential clinical and crew health end states are established to generate end state probabilities. A Monte Carlo computational method is used to determine the probable outcomes and requires up to 25,000 mission trials to reach convergence. For each mission trial, the pharmaceuticals and supplies required to diagnose and treat prevalent medical conditions are tracked and decremented. The uncertainty of patient response to treatment is bounded via a best-case, worst-case, untreated case algorithm. A Crew Health Index (CHI) metric, developed to account for functional impairment due to a medical condition, provides a quantified measure of risk and enables risk comparisons across mission scenarios. The use of historical in-flight medical data, terrestrial surrogate data as appropriate, and space medicine subject matter expertise has enabled the development of a probabilistic, stochastic decision support tool capable of optimizing in-flight medical systems based on crew and mission parameters. This presentation will illustrate how to apply quantitative risk assessment methods to optimize the mass and volume of space-based medical systems for a space flight mission given the level of crew health and mission risk.

Kerstman, Eric↗
NASA NTRS2005

Using Remote Sensing Data to Evaluate Surface Soil Properties in Alabama Ultisols

Evaluation of surface soil properties via remote sensing could facilitate soil survey mapping, erosion prediction and allocation of agrochemicals for precision management. The objective of this study was to evaluate the relationship between soil spectral signature and surface soil properties in conventionally managed row crop systems. High-resolution RS data were acquired over bare fields in the Coastal Plain, Appalachian Plateau, and Ridge and Valley provinces of Alabama using the Airborne Terrestrial Applications Sensor multispectral scanner. Soils ranged from sandy Kandiudults to fine textured Rhodudults. Surface soil samples (0-1 cm) were collected from 163 sampling points for soil organic carbon, particle size distribution, and citrate dithionite extractable iron content. Surface roughness, soil water content, and crusting were also measured during sampling. Two methods of analysis were evaluated: 1) multiple linear regression using common spectral band ratios, and 2) partial least squares regression. Our data show that thermal infrared spectra are highly, linearly related to soil organic carbon, sand and clay content. Soil organic carbon content was the most difficult to quantify in these highly weathered systems, where soil organic carbon was generally less than 1.2%. Estimates of sand and clay content were best using partial least squares regression at the Valley site, explaining 42-59% of the variability. In the Coastal Plain, sandy surfaces prone to crusting limited estimates of sand and clay content via partial least squares and regression with common band ratios. Estimates of iron oxide content were a function of mineralogy and best accomplished using specific band ratios, with regression explaining 36-65% of the variability at the Valley and Coastal Plain sites, respectively.

Sullivan, Dana G.↗
NASA NTRS2011

Dynamic Monitoring of Cleanroom Fallout Using an Air Particle Counter

The particle fallout limitations and periodic allocations for the James Webb Space Telescope are very stringent. Standard prediction methods are complicated by non-linearity and monitoring methods that are insufficiently responsive. A method for dynamically predicting the particle fallout in a cleanroom using air particle counter data was determined by numerical correlation. This method provides a simple linear correlation to both time and air quality, which can be monitored in real time. The summation of effects provides the program better understanding of the cleanliness and assists in the planning of future activities. Definition of fallout rates within a cleanroom during assembly and integration of contamination-sensitive hardware, such as the James Webb Space Telescope, is essential for budgeting purposes. Balancing the activity levels for assembly and test with the particle accumulation rate is paramount. The current approach to predicting particle fallout in a cleanroom assumes a constant air quality based on the rated class of a cleanroom, with adjustments for projected work or exposure times. Actual cleanroom class can also depend on the number of personnel present and the type of activities. A linear correlation of air quality and normalized particle fallout was determined numerically. An air particle counter (standard cleanroom equipment) can be used to monitor the air quality on a real-time basis and determine the "class" of the cleanroom (per FED-STD-209 or ISO-14644). The correlation function provides an area coverage coefficient per class-hour of exposure. The prediction of particle accumulations provides scheduling inputs for activity levels and cleanroom class requirements.

Perry, Radford↗
NASA NTRS1994

Advanced technology for a satellite multichannel demultiplexer/demodulator

Satellite on-board processing is needed to efficiently service multiple users while at the same time minimizing earth station complexity. The processing satellite receives a wideband uplink at 30 GHz and down-converts it to a suitable intermediate frequency. A multichannel demultiplexer then separates the composite signal into discrete channels. Each channel is then demodulated by bulk demodulators, with the baseband signals routed to the downlink processor for retransmission to the receiving earth stations. This type of processing circumvents many of the difficulties associated with traditional bent-pipe repeater satellites. Uplink signal distortion and interference are not retransmitted on the downlink. Downlink power can be allocated in accordance with user needs, independent of uplink transmissions. This allows the uplink users to employ different data rates as well as different modulation and coding schemes. In addition, all downlink users have a common frequency standard and symbol clock on the satellite, which is useful for network synchronization in time division multiple access schemes. The purpose of this program is to demonstrate the concept of an optically implemented multichannel demultiplexer (MCD). A proof-of-concept (POC) model has been developed which has the ability to receive a 40 MHz wide composite signal consisting of up to 1000 40 kHz QPSK modulated channels and perform the demultiplexing process. In addition a set of special test equipment (STE) has been configured to evaluate the performance of the POC model. The optical MCD is realized as an acousto-optic spectrum analyzer utilizing the capability of Bragg cells to perform the required channelization. These Bragg cells receive an optical input from a laser source and an RF input (the signal). The Bragg interaction causes optical output diffractions at angles proportional to the RF input frequency. These discrete diffractions are optically detected and output to individual demodulators for baseband conversion. Optimization of the MCD design was conducted in order to achieve a compromise between two opposing sources of signal degradation: adjacent channel interference and intersymbol interference. The system was also optimized to allow simple, inexpensive ground stations communications with the MCD. These design goals led to the realization of a POC MCD which demonstrates the demultiplexing function with minimal signal degradation. Performance evaluation results using the STE equipment indicate that the dynamic range of the demultiplexer in the presence of adjacent and multiple channel loading is 40 - 50 dB. Measured bit error rate (BER) probabilities varied from the predicted theoretical results by one dB or less. The performance of the proof-of-concept model indicate that the development of a space qualified optically implemented MCD are feasible. The advantages to such an implementation include reduced size, weight and power and increased reliability when compared with electronic approaches. All of these factors are critical to on-board satellite processors. Further optimization can be conducted which trade ground station complexity and MCD performance to achieve desired system results.

Abramovitz, Irwin J.↗
NASA NTRS2016

Experiences with Extra-Vehicular Activities in Response to Critical ISS Contingencies

The maturation of the International Space Station (ISS) design from the proposed Space Station Freedom to today's current implementation resulted in external hardware redundancy vulnerabilities in the final design. Failure to compensate for or respond to these vulnerabilities could put the ISS in a posture to where it could no longer function as a habitable space station. In the first years of ISS assembly, these responses were to largely be addressed by the continued resupply and Extra-Vehicular Activity (EVA) capabilities of the Space Shuttle. Even prior to the decision to retire the Space Shuttle, it was realized that ISS needed to have its own capability to be able to rapidly repair or replace external hardware without needing to wait for the next cargo resupply mission. As documented in a previous publicatoin5, in 2006 development was started to baseline Extra- Vehicular Activity (EVA, or spacewalk) procedures to replace hardware components whose failure would expose some of the ISS vulnerabilities should a second failure occur. This development work laid the groundwork for the onboard crews and the ground operations and engineering teams to be ready to replace any of this failed hardware. In 2010, this development work was put to the test when one of these pieces of hardware failed. This paper will provide a brief summary of the planning and processes established in the original Contingency EVA development phase. It will then review how those plans and processes were implemented in 2010, highlighting what went well as well as where there were deficiencies between theory and reality. This paper will show that the original approach and analyses, though sound, were not as thorough as they should have been in the realm of planning for next worse failures, for documenting Programmatic approval of key assumptions, and not pursuing sufficient engineering analysis prior to the failure of the hardware. The paper will further highlight the changes made to the Contingency EVA preparation team structure, approach, goals, and the resources allocated to its work after the 2010 events. Finally, the authors will overview the implementation of these updates in addressing failures onboard the ISS in 2012, 2013, and 2014. The successful use of the updated approaches, and the application of the approaches to other spacewalks, will demonstrate the effectiveness of this additional work and make a case for putting significant time and resources into pre-failure planning and analysis for critical hardware items on human-tended spacecraft.

Van Cise, E. A.↗
NASA NTRS2016

Experiences with Extra-Vehicular Activities in Response to Critical ISS Contingencies

The maturation of the International Space Station (ISS) design from the proposed Space Station Freedom to today's current implementation resulted in external hardware redundancy vulnerabilities in the final design. Failure to compensate for or respond to these vulnerabilities could put the ISS in a posture where it could no longer function as a habitable space station. In the first years of ISS assembly, these responses were to largely be addressed by the continued resupply and Extra-Vehicular Activity (EVA) capabilities of the Space Shuttle. Even prior to the decision to retire the Space Shuttle, it was realized that ISS needed to have its own capability to be able to rapidly repair or replace external hardware without needing to wait for the next cargo resupply mission. As documented in a previous publication, in 2006 development was started to baseline Extra-Vehicular Activity (EVA, or spacewalk) procedures to replace hardware components whose failure would expose some of the ISS vulnerabilities should a second failure occur. This development work laid the groundwork for the onboard crews and the ground operations and engineering teams to be ready to replace any of this failed hardware. In 2010, this development work was put to the test when one of these pieces of hardware failed. This paper will provide a brief summary of the planning and processes established in the original Contingency EVA development phase. It will then review how those plans and processes were implemented in 2010, highlighting what went well as well as where there were deficiencies between theory and reality. This paper will show that the original approach and analyses, though sound, were not as thorough as they should have been in the realm of planning for next worse failures, for documenting Programmatic approval of key assumptions, and not pursuing sufficient engineering analysis prior to the failure of the hardware. The paper will further highlight the changes made to the Contingency EVA preparation team structure, approach, goals, and the resources allocated to its work after the 2010 events. Finally, the authors will overview the implementation of these updates in addressing failures onboard the ISS in 2012, 2013, and 2014. The successful use of the updated approaches, and the application of the approaches to other spacewalks, will demonstrate the effectiveness of this additional work and make a case for putting significant time and resources into pre-failure planning and analysis for critical hardware items on human-tended spacecraft.

Van Cise, E. A.↗
NASA NTRS2016

Development and Characterization of a Small Spacecraft Electro-Optic Scanner for Free-Space Laser Communications

Emergent data-intensive missions coupled with dramatic reductions in spacecraft size plus an increasing number of space-based missions necessitates new high performance, compact and low cost communications technology. Free space optical communications offer advantages including orders of magnitude increase for data rate performance, increased security, immunity to jamming and lack of frequency allocation requirements when compared with conventional radio frequency (RF) means. The spatial coherence and low divergence associated with the optical frequencies of laser communications lends themselves to superior performance, but this increased directionality also creates one of the primary technical challenges in establishing a laser communications link by repeatedly and reliably pointing the beam onto the receive aperture. Several solutions have emerged from wide angle (slow) mechanical articulation systems, fine (fast) steering mirrors and rotating prisms, inertial compensation gyros and vibration isolation cancellation systems, but each requires moving components and imparts a measured amount of burden on the host platform. The complexity, cost and size of current mechanically scanned solutions limits their platform applicability, and restricts the feasibility of deploying optical communications payloads on very compact spacecraft employing critical systems. A high speed, wide angle, non-mechanical solution is therefore desirable. The purpose of this work is to share the development, testing, and demonstration of a breadboard prototype electro-optic (EO) scanned laser-communication link (see Figure 1). This demonstration is a step toward realizing ultra-low Size, Weight and Power (SWaP) SmallSat/MicroSat EO non-mechanical laser beam steering modules for high bandwidth ( greater than Gbps) free-space data links operating in the 1550 nm wavelength bands. The elimination of all moving parts will dramatically reduce SWaP and cost, increase component lifetime and reliability, and simplify the system design of laser communication modules. This paper describes the target mission architectures and requirements (few cubic centimeters of volume, 10's of grams of weight with milliwatts of power) and design of the beam steering module. Laboratory metrology is used to determine the component performance including horizontal and vertical resolution (20urad) as a function of control voltage (see Figure 2), transition time (0.1-1ms), pointing repeatability and optic insertion loss. A test bed system demonstration, including a full laser communications link, is conducted. The capabilities of this new EO beam steerer provide an opportunity to dramatically improve space communications through increased utilization of laser technology on smaller platforms than were previously attainable.

Laser Optical Communications↗
NASA NTRSDate not supplied

A Science-Focused Artificial Intelligence (AI) Responding in Real-Time to New Information: Capability Demonstration for Ocean World Missions

Introduction: Artificial intelligence (AI) has long been considered a potential mechanism to explore increasingly challenging environments, including those with extreme temperatures and pressures, limited communication capabilities, or those with demanding terrain. We posit that missions in extreme environments could deploy an onboard AI focused on science observations and goals in order to augment a traditional concept(s) of operations (ConOps). An onboard AI capability could perform functions such as data analysis in order to make high-level decisions, including prioritized data transmission for analysis by ground-based teams or autonomously-guided follow-on analyses that maximize science return. Such a capability would empower missions to respond to scientific data of interest in real-time; a mission could make observations and perform a preliminary analysis to alert ground-based scientists to an observation of interest, enabling an informed, rapid response from Earth-based teams. Enceladus Case Study for Onboard AI: We are developing an onboard AI capability for real-time telemetry response that formulates and carries-out informed decisions in service to established mission goals, enabling increased science return of a mission. We focus our AI development for use on a constellation of SmallSats orbiting Enceladus. Our Enceladus case study tests autonomous decision-making capabilities in scenarios with complex orbital dynamics, plume ejecta, extreme cold environments, power restrictions, and a requirement to maximize science return for a potential positive detection of life, while critically evaluating the potential for false positives. Telemetry includes simulated scientific data, spacecraft onboard operational data (e.g., position, velocity, and rotation), and engineering hardware performance data. Enceladus SmallSat Constellation. Our constellation includes eight SmallSat spacecraft in an 8:35 resonant orbit-based formation, leveraging Saturn’s gravitational forces to maintain stable orbits with global coverage around Enceladus. To our knowledge, we simulate the first stable configuration of multiple spacecraft in closed orbits around Enceladus, using a full ephemeris force model (Russell and Lara, 2009). Each spacecraft’s orbit will precess, causing an eastward ground track shift (from an orbiter’s perspective) of each spacecraft for each orbit. However, all spacecraft return to their original positions relative to Enceladus after eight Enceladus revolutions around Saturn. We model communication pathways between SmallSats to understand how information would need to be transmitted across the constellation to enable AI-driven decision-making and resource allocation across the fleet. Capability Demonstration. Our simulated capability demonstration inputs position, velocity, and rotation telemetry from our Enceladus-focused constellation simulations, and mass spectrometry data collected from abiotic and biotic laboratory-analog ocean world experiments (Theiling et al., 2018; Theiling, 2021; Da Poian et al., 2023). Data from these experiments are used to simulate MS measurements and different scenarios of science observations for onboard analysis performed on each of the eight spacecraft. For these demonstrations, we integrate 24 machine learning (ML) algorithms into an onboard intelligence as a ‘knowledge base’, including algorithms evaluating data quality and those predicting (with % confidence) gas composition, ocean aqueous chemistry, and whether the sample was influenced by microbial life. The onboard AI capability is designed to use the knowledge base to come to a consensus-based decision in the interpretation of the observed data in order to request additional action outside of a pre-defined ConOps. Requested actions could include e.g., prioritized downlink to Earth (for analysis by ground-based teams) or follow-on analyses performed across the constellation. The spacecraft’s intelligent onboard planner must then determine whether sufficient resources (e.g., time, power, etc.) are available and weigh the request with mission priorities. In our simulation, the constellation is able to identify potential biosignatures using onboard ML algorithms, evaluate the confidence of that prediction, and perform follow-on analyses across the fleet to confirm the detection, in order to best prepare a transmission of these data to Earth-based teams.

astrobiology↗
NASA NTRS2019

Predictive Modeling for Differential Diagnosis and Mortality Risk Assessment

The prevalence of electronic health record (EHR) systems has brought prodigious biomedical informatics opportunity. Automated machine learning methods can effectively utilize such data and have become common tools for healthcare predictive modeling. Researches in medical informatics have explored the potential of deep learning and classical models in emergent care scenarios. In particular, predicting differential diagnoses for admissions have proven useful in decreasing unnecessary lab tests and improving inpatient triage decision-making. Moreover, identification of high-risk patients for in-hospital mortality is vitally important to maximize allocation of medical resources.The Medical Information Mart for Intensive Care (MIMIC-III) database, containing de-identified critical care inpatient was used in our study. This data set captures hospital patient laboratory measurements, pharmacologic prescriptions, diagnostic data and procedure event recordings. When considering adult patients and discounting admissions with ICU length of stay less than 24 hours, there were 37,787 unique admissions and 30,414 total patients. We examined the top 25 most prevalent ICD-9 group-level disease specificities in MIMIC-III using a multi-label classification model. In-hospital mortality was modeled as binary classification with 4,155 (13%) adult patients that expired, of which 3,138 (75.5%) were in the ICU setting. The metrics AUC, F1 score, sensitivity and specificity values calculated for each disease label measured prediction performance.The usage of ICD-9 group codes reduced feature dimension from 14,567 to 942 and greatly improved distribution of patient diagnostic categories. Disease temporal patterns were captured by considering the most frequently sampled 6 vital signs and 13 laboratory values. Missing data were imputed at each time-stamp. Time-series raw hourly average values were converted into 5 summary features (mean, standard deviation, number of observations, min & max values). Patient demographic variables such as age, gender, marital status and ethnicity were also factored into the modeling. Choi et al showed that contextual embedding of medical data, diagnostic and procedural codes alone can predict future diagnoses with sensitivity as high as 0.79. We utilized an embedding technique called word2vec which allowed sparse representations of medical history to be transformed into dense word vectors. The mappings captured contextual information by treating each admission as a sentence and learning the most likely neighboring words in a sliding window fashion. Binary and multi-label classification was achieved via collapse models, which do not consider temporal information, as well as recurrent neural networks with regularization, Softmax output layer activation together with categorical cross-entropy as the loss function.

US Army collaboration↗
NASA NTRS1999

The MSP 2001 Mars Environmental Compatibility Assessment (MECA)

A chemical analysis of soil-water mixtures and the first microscopic images of martian soil will be among the results to be returned by the Mars Environmental Compatibility Assessment (MECA) payload on the Mars Surveyor Program 2001 Lander. Sponsored by the Human Exploration and Development of Space (HEDS) enterprise, MECA's primary goal is to evaluate potential geochemical and environmental hazards that may confront future martian explorers, and to guide HEDS scientists in the development of high fidelity Mars soil simulants. As a survey of soil properties, the MECA data set will also be rich in information relevant to basic geology, paleoclimate, and exobiology. The integrated MECA payload contains a wet-chemistry laboratory, a microscopy station, an electrometer to characterize the electrostatics of the soil and its environment, and arrays of material patches to study the abrasive and adhesive properties of soil grains. MECA is allocated a mass of 10 kg and a peak power usage of 15 W within an enclosure of 35 x 25 x 15 cm. The Wet Chemistry Laboratory (WCL) consists of four identical cells that will accept samples from surface and subsurface regions accessible to the Lander's robotic arm, mix them with water, and perform extensive analysis of the solution. Ion-selective electrodes and related sensors will evaluate total dissolved solids, redox potential, pH, and the concentration of many soluble ions and gases. Cyclic voltammetry will address oxidants, and anodic stripping voltammetry will probe potentially hazardous trace metals. MECA's microscopy station combines optical and atomic-force microscopy (AFM) in a controlled illumination environment to image dust and soil particles from millimeters to nanometers in size. Careful selection of substrates and an abrasion tool allows experimental study of size distribution, adhesion, abrasion, hardness, color, shape, aggregation, magnetic and other properties. Mounted on the end of the robot arm, MECA's electrometer consists of four types of sensors: an electric field meter, several triboelectricity monitors, an ion gauge, and a thermometer. Tempered only by ultra-violet- light-induced ions and a low-voltage break-down threshold, the dry, cold, dusty martian environment presents an imposing electrostatic hazard to both robots and humans. In addition, the electrostatic environment is key to transport of dust and, consequently, martian meteorology. MECA will also observe natural dust accumulation on engineering materials. Viewed with the robot arm camera, the abrasion and adhesion plates are strategically placed to allow direct observation of the inter-action between materials and soils on a macroscopic scale. Materials of graded hardness are placed directly under the robot arm scoop to sense wear and soil hardness. A second array, placed on the lander deck, is deployed after the dust plume of landing has settled. It can be manipulated in a primitive fashion by the arm, first having dirt deposited on it from the scoop and subsequently shaken clean. Dust accumulation as a function of conductivity, magnetic field strength, and other parameters will be explored. The MECA instruments described above will assess potential hazards that the Martian soil might present to human explorers and their equipment. In addition, MECA will provide information on the composition of ancient surface water environments, observing microscopic evidence of geological (and biological?) processes, inferring soil and dust transport, comminution and weathering mechanisms, and characterizing soil horizons that might be encountered during excavation. Additional information is contained in the original extended abstract.

Hecht, M. H.↗
NASA NTRS1999

Angiotensin-converting enzyme and matrix metalloproteinase inhibition with developing heart failure: comparative effects on left ventricular function and geometry

The progression of congestive heart failure (CHF) is left ventricular (LV) myocardial remodeling. The matrix metalloproteinases (MMPs) contribute to tissue remodeling and therefore MMP inhibition may serve as a useful therapeutic target in CHF. Angiotensin converting enzyme (ACE) inhibition favorably affects LV myocardial remodeling in CHF. This study examined the effects of specific MMP inhibition, ACE inhibition, and combined treatment on LV systolic and diastolic function in a model of CHF. Pigs were randomly assigned to five groups: 1) rapid atrial pacing (240 beats/min) for 3 weeks (n = 8); 2) ACE inhibition (fosinopril, 2.5 mg/kg b.i.d. orally) and rapid pacing (n = 8); 3) MMP inhibition (PD166793 2 mg/kg/day p.o.) and rapid pacing (n = 8); 4) combined ACE and MMP inhibition (2.5 mg/kg b.i.d. and 2 mg/kg/day, respectively) and rapid pacing (n = 8); and 5) controls (n = 9). LV peak wall stress increased by 2-fold with rapid pacing and was reduced in all treatment groups. LV fractional shortening fell by nearly 2-fold with rapid pacing and increased in all treatment groups. The circumferential fiber shortening-systolic stress relation was reduced with rapid pacing and increased in the ACE inhibition and combination groups. LV myocardial stiffness constant was unchanged in the rapid pacing group, increased nearly 2-fold in the MMP inhibition group, and was normalized in the ACE inhibition and combination treatment groups. Increased MMP activation contributes to the LV dilation and increased wall stress with pacing CHF and a contributory downstream mechanism of ACE inhibition is an effect on MMP activity.

Non-NASA Center↗