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COMPASS Final Report: Radioisotope Electric Propulsion (REP) Centaur Orbiter New Frontiers Mission
Radioisotope Electric Propulsion (REP) has been shown in past studies to enable missions to outer planetary bodies including the orbiting of Centaur asteroids. Key to the feasibility for REP missions are long life, low power electric propulsion (EP) devices, low mass Radioisotope Power System (RPS) and light spacecraft (S/C) components. In order to determine the key parameters for EP devices to perform these REP missions a design study was completed to design an REP S/C to orbit a Centaur in a New Frontiers (NF) cost cap. The design shows that an orbiter using several long lived (approx.200 kg xenon (Xe) throughput), low power (approx.700 W) Hall thrusters teamed with six (150 W each) Advanced Stirling Radioisotope Generators (ASRG) can deliver 60 kg of science instruments to a Centaur in 10 yr within the NF cost cap. Optimal specific impulses (Isp) for the Hall thrusters were found to be around 2000 s with thruster efficiencies over 40 percent. Not only can the REP S/C enable orbiting a Centaur (when compared to an all chemical mission only capable of flybys) but the additional power from the REP system can be used to enhance science and simplify communications. The mission design detailed in this report is a Radioisotope Power System (RPS) powered EP science orbiter to the Centaur Thereus with arrival 10 yr after launch, ending in a 1 yr science mapping mission. Along the trajectory, approximately 1.5 yr into the mission, the REP S/C does a flyby of the Trojan asteroid Tlepolemus. The total (Delta)V of the trajectory is 8.9 km/s. The REP S/C is delivered to orbit on an Atlas 551 class launch vehicle with a Star 48 B solid rocket stage
COMPASS Final Report: Lunar Network Satellite-High Rate (LNS-HR)
Two design options were explored to address the requirement to provide lunar piloted missions with continuous communications for outpost and sortie missions. Two unique orbits were assessed, along with the appropriate spacecraft (S/C) to address these requirements. Both constellations (with only two S/C each) provide full time coverage (24 hr/7 d) for a south polar base and also provide continuous 7 day coverage for sorties for specified sites and periodic windows. Thus a two-satellite system can provide full coverage for sorties for selected windows of opportunity without reconfiguring the constellation.
NASA GRC Compass Team Conceptual Point Design and Trades of a Hybrid Solar Electric Propulsion (SEP)/Chemical Propulsion Human Mars Deep Space Transport (DST) Vehicle
NASA has long been conducting studies which apply different in-space propulsion technology assumptions to the mission of sending humans to Mars. Two of the technologies under study that are considered to be the most near-term with respect to technology readiness level (TRL) are traditional chemical propulsion systems and high-power Solar Electric Propulsion (SEP) systems. The benefit of relatively low trip times inherent in using impulsive chemical propulsion systems to perform the full round-trip delta V is hampered by the large propellant mass required to perform these burns for human Mars missions. SEP systems offer the benefit of much lower propellant requirements to perform the same round-trip missions, at the cost of longer trip times. Traditionally, impulsive chemical systems are better suited than SEP when used in a gravity well, and SEP systems are more efficient than traditional impulsive systems when used in interplanetary space. A mission to Mars includes both of these scenarios, and thus several NASA architecture studies performed over the last few years have looked to combine the use of both SEP and chemical propulsion systems where they are the most beneficial to human Mars missions. This combined propulsion system concept has been referred to as a SEP/Chem hybrid Mars Transfer Vehicle and is currently shown as the concept Deep Space Transport (DST) in the March 2017 NASA presentation to the National Aerospace Council (NAC).
Compass Final Report: Nuclear Electric Propulsion (NEP)-Chemical Vehicle 1.2
Many previous studies have examined sending crews to and from Mars. The most economical involved a ‘conjunction’ class whereby the crew spends around 500 days on Mars waiting for a ‘cheap’ return. The total mission time results in over a 1000-day mission duration (about 3 years). Given the current experience level of only one year on the International Space Station (ISS), it of interest to reduce that time to only two years, thus reducing risk and minimizing required Mars surface infrastructure. The Phase 1.1 Study goal was stated as follows, “Determine the feasibility of a two-year roundtrip class Mars mission concept of operation that enables boots on Mars no later than 2036.” While the Phase1 study did show feasibility for the NEP-Chemical option, the 2036 Opposition opportunity was found to stress the schedule due to proposed technology development schedules. A 2039 Opposition (which requires even more energy than the 2036 case) was chosen as representative for Phase 1.2. Phase 1.2 also sought to further refine the concept, building on the feasibility, but addressing several challenges brought by the red team and habitat team. Given the date of 2039, nearer term technologies, primarily nuclear thermal and nuclear electric were deemed as the most viable for these missions. As will be shown, the energy required to perform such a mission in only two years (for the 2039 opportunity at least) is about three times that of the three-year conjunction mission. The rocket equation shows that this mission would then require several times the propellant of the three-year mission unless the specific impulse (ISP) of the propulsion system can be increased. Based on lunar needs, a limit of five Space Launch System (SLS) launchers with 8.4m fairings was imposed for the piloted transportation portion of the mission, limiting the size of the system. When using nuclear electric propulsion, the main limiting factor was packaging the required radiator area. The higher Isp nuclear electric propulsion (NEP) system option is described herein but with a twist: in order to keep the size of radiators packageable in one SLS and use proven reactor power system technology (~1200K reactor outlet temperature and superalloy-class Brayton) the NEP system had to be combined with a chemical propulsion system. This combination of electric propulsion and high thrust chemical was found to be useful in previous design studies combining solar electric propulsion (SEP) and chemical propulsion. Such a combination allowed the low-thrust system to provide significant change in velocity (∆V) during the interplanetary portions of the mission, thereby notably reducing the ∆V required by the high thrust system to capture and depart from the Mars gravity well. Here the high thrust ‘impulsive’ system is more efficient due to the Oberth Effect. A plethora of trades, both at the mission and system level, as well as the subsystem level were performed to develop these vehicle concepts. An entire family of NEP-Chemical transportation vehicles is described herein. The main driver and the primary focus was the piloted vehicle but additional concepts for cargo were performed using the same ‘building blocks’ in order to reduce costs and provide commonality.
Compass Concurrent Engineering Lessons Learned in Remote and Hybrid Environments
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COMPASS: A New COnductance Model Based on PFISR And SWARM Satellite Observations
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JWST COMPASS: NIRSpec/G395H Transmission Observations of TOI-776 c, a 2 R ⊕ M Dwarf Planet
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Sci—Fri PM: Dosimetry—06: Commissioning of a 3D patient specific QA system for hypofractionated prostate treatments
The objective of this work is to commission the 6MV-SRS beam model in COMPASS (v2.1, IBA-Dosimetry) and validate its use for patient specific QA of hypofractionated prostate treatments. The COMPASS system consists of a 2D ion chamber array (MatriXX{sup Evolution}), an independent gantry angle sensor and associated software. The system can either directly calculate or reconstruct (using measured detector responses) a 3D dose distribution on the patient CT dataset for plan verification. Beam models are developed and commissioned in the same manner as a beam model is commissioned in a standard treatment planning system. Model validation was initially performed by comparing both COMPASS calculations and reconstructions to measured open field beam data. Next, 10 hypofractionated prostate RapidArc plans were delivered to both the COMPASS system and a phantom with ion chamber and film inserted. COMPASS dose distributions calculated and reconstructed on the phantom CT dataset were compared to the chamber and film measurements. The mean (± standard deviation) difference between COMPASS reconstructed dose and ion chamber measurement was 1.4 ± 1.0%. The maximum discrepancy was 2.6%. Corresponding values for COMPASS calculation were 0.9 ± 0.9% and 2.6%, respectively. The average gamma agreement index (3%/3mm) for COMPAS reconstruction and film was 96.7% and 95.3% when using 70% and 20% dose thresholds, respectively. The corresponding values for COMPASS calculation were 97.1% and 97.1%, respectively. Based on our results, COMPASS can be used for the patient specific QA of hypofractionated prostate treatments delivered with the 6MV-SRS beam.
SU-F-T-549: Validation of a Method for in Vivo 3D Dose Reconstruction for SBRT Using a New Transmission Detector
Purpose: Recently, there has been increased clinical use of stereotactic body radiation therapy (SBRT). SBRT treatments will strongly benefit from in vivo patient dose verification, as any errors in delivery can be more detrimental to the radiobiology of the patient as compared to conventional therapy. In vivo dose measurements, a commercially available quality assurance platform which is able to correlate the delivered dose to the patient’s anatomy and take into account tissue inhomogeneity, is the COMPASS system (IBA Dosimetry, Germany) using a new transmission detector (Dolphin, IBA Dosimetry). In this work, we evaluate a method for in vivo 3D dose reconstruction for SBRT using a new transmission detector, which was developed for in vivo dose verification for intensity-modulated radiation therapy (IMRT). Methods: We evaluated the accuracy of measurement for SBRT using simple small fields (2×2−10×10 cm2), a multileaf collimator (MLC) test pattern, and clinical cases. The dose distributions from the COMPASS were compared with those of EDR2 films (Kodak, USA) and the Monte Carlo simulations (MC). For clinical cases, we compared MC using dose-volume-histograms (DVHs) and dose profiles. Results: The dose profiles from the COMPASS for small fields and the complicated MLC test pattern agreed with those of EDR2 films, and MC within 3%. This showed the COMPASS with Dolphin system showed good spatial resolution and can measure small fields which are required for SBRT. Those results also suggest that COMPASS with Dolphin is able to detect MLC leaf position errors for SBRT. In clinical cases, the COMPASS with Dolphin agreed well with MC. The Dolphin detector, which consists of ionization chambers, provided stable measurement. Conclusion: COMPASS with Dolphin detector showed a useful in vivo 3D dose reconstruction for SBRT. The accuracy of the results indicates that this approach is suitable for clinical implementation.
Comparison of 3-dimensional dose reconstruction system between fluence-based system and dose measurement-guided system
COMPASS system (IBA Dosimetry, Schwarzenbruck, Germany) and ArcCHECK with 3DVH software (Sun Nuclear Corp., Melbourne, FL) are commercial quasi-3-dimensional (3D) dosimetry arrays. Cross-validation to compare them under the same conditions, such as a treatment plan, allows for clear evaluation of such measurement devices. In this study, we evaluated the accuracy of reconstructed dose distributions from the COMPASS system and ArcCHECK with 3DVH software using Monte Carlo simulation (MC) for multi-leaf collimator (MLC) test patterns and clinical VMAT plans. In a phantom study, ArcCHECK 3DVH showed clear differences from COMPASS, measurement and MC due to the detector resolution and the dose reconstruction method. Especially, ArcCHECK 3DVH showed 7% difference from MC for the heterogeneous phantom. ArcCHECK 3DVH only corrects the 3D dose distribution of treatment planning system (TPS) using ArcCHECK measurement, and therefore the accuracy of ArcCHECK 3DVH depends on TPS. In contrast, COMPASS showed good agreement with MC for all cases. However, the COMPASS system requires many complicated installation procedures such as beam modeling, and appropriate commissioning is needed. In terms of clinical cases, there were no large differences for each QA device. The accuracy of the compass and ArcCHECK 3DVH systems for phantoms and clinical cases was compared. Both systems have advantages and disadvantages for clinical use, and consideration of the operating environment is important. The QA system selection is depending on the purpose and workflow in each hospital.
SU-E-T-77: Comparison of 2D and 3D Gamma Analysis in Patient-Specific QA for Prostate VMAT Plans
Purpose: Patient-specific QA procedures for IMRT and VMAT are traditionally performed by comparing TPS calculations with measured single point values and plane dose distributions by means of gamma analysis. New QA devices permit us to calculate 3D dose distributions on patient anatomy as redundant secondary check and reconstruct it from measurements taken with 2D and 3D detector arrays. 3D dose calculations allow us to perform DVH-based comparisons with clinical relevance, as well as 3D gamma analysis. One of these systems (Compass, IBA Dosimetry) combines traditional 2D with new anatomical-based 3D gamma analysis. This work shows the ability of this system by comparing 2D and 3D gamma analysis in pre-treatment QA for several VMAT prostate plans. Methods: Compass is capable of calculating dose as secondary check from DICOM TPS data and reconstructing it from measurements taken by a 2D ion chamber array (MatriXX Evolution, IBA Dosimetry). Both 2D and 3D gamma tests are available to compare calculated and reconstructed dose in Compass with TPS RT Dose. Results: 15 VMAT prostate plans have been measured with Compass. Dose is reconstructed with Compass for these plans. 2D gamma comparisons can be done for any plane from dose matrix. Mean gamma passing rates for isocenter planes (axial, coronal, sagittal) are (99.7±0.2)%, (99.9±0.1)%, (99.9±0.1)% for reconstructed dose planes. 3D mean gamma passing rates are (98.5±1.7)% for PTVs, (99.1±1.5)% for rectum, (100.0±0.0)% for bladder, (99.6±0.7)% for femoral heads and (98.1±4.1)% for penile bulb. Conclusion: Compass is a powerful tool to perform a complete pre-treatment QA analysis, from 2D techniques to 3D DVH-based techniques with clinical relevance. All reported values for VMAT prostate plans are in good agreement with TPS values. This system permits us to ensure the accuracy in the delivery of VMAT treatments completing a full patient-specific QA program.
Spin relaxation of radicals in cryptochrome and its role in avian magnetoreception
Long-lived spin coherence and rotationally ordered radical pairs have previously been identified as key requirements for the radical pair mechanism of the avian magnetic compass sense. Both criteria are hard to meet in a biological environment, where thermal motion of the radicals creates dynamic disorder and drives efficient spin relaxation. This has long been cited as a major stumbling block of the radical pair hypothesis. Here we combine Redfield relaxation theory with analytical solutions to a rotational diffusion equation to assess the impact of restricted rotational motion of the radicals on the operation of the compass. The effects of such motions are first investigated generally in small, model systems and are then critically examined in the magnetically sensitive flavin-tryptophan radical pair that is formed photochemically in the proposed magnetoreceptor protein, cryptochrome. We conclude that relaxation is slowest when rotational motion of the radicals within the protein is fast and highly constrained; that in a regime of slow relaxation, the motional averaging of hyperfine interactions has the potential to improve the sensitivity of the compass; and that consideration of motional effects can significantly alter the design criteria for an optimal compass. In addition, we demonstrate that motion of the flavin radical is likely to be compatible with its role as a component of a functioning radical-pair compass, whereas the motion of the tryptophan radical is less ideal, unless it is particularly fast.
Combined Mesonet and Tracker
Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (°C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a “0” if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the “time warp” period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046–1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503–2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100–103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278–283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]
Methodologies for building robust schedules
COMPASS is the name of a Computer Aided Scheduling System designed and built for NASA. COMPASS can be used to develop schedule of activities based upon the temporal relationships of the activities and their resource requirements. COMPASS uses this information, and guided by the user, develops precise start and stop times for the activities. In actual practice however, it is impossible to know with complete certainty what the actual durations of the scheduled activities will really be. The best that one can hope for is knowledge of the probability distribution for the durations. This paper investigates methodologies for using a scheduling tool like COMPASS that is based upon definite values for the resource requirements, while building schedules that remain valid in the face of the schedule execution perturbations. Representations for the schedules developed by these methodologies are presented, along with a discussion of the algorithm that could be used by a computer onboard a spacecraft to efficiently monitor and execute these schedules.
The Autonomic Symptom Profile: a new instrument to assess autonomic symptoms
OBJECTIVE: To develop a new specific instrument called the Autonomic Symptom Profile to measure autonomic symptoms and test its validity. BACKGROUND: Measuring symptoms is important in the evaluation of quality of life outcomes. There is no validated, self-completed questionnaire on the symptoms of patients with autonomic disorders. METHODS: The questionnaire is 169 items concerning different aspects of autonomic symptoms. The Composite Autonomic Symptom Scale (COMPASS) with item-weighting was established; higher scores indicate more or worse symptoms. Autonomic function tests were performed to generate the Composite Autonomic Scoring Scale (CASS) and to quantify autonomic deficits. We compared the results of the COMPASS with the CASS derived from the Autonomic Reflex Screen to evaluate validity. RESULTS: The instrument was tested in 41 healthy controls (mean age 46.6 years), 33 patients with nonautonomic peripheral neuropathies (mean age 59.5 years), and 39 patients with autonomic failure (mean age 61.1 years). COMPASS scores correlated well with the CASS, demonstrating an acceptable level of content and criterion validity. The mean (+/-SD) overall COMPASS score was 9.8 (+/-9) in controls, 25.9 (+/-17.9) in the patients with nonautonomic peripheral neuropathies, and 52.3 (+/-24.2) in the autonomic failure group. Scores of symptoms of orthostatic intolerance and secretomotor dysfunction best predicted the CASS on multiple stepwise regression analysis. CONCLUSIONS: We describe a questionnaire that measures autonomic symptoms and present evidence for its validity. The instrument shows promise in assessing autonomic symptoms in clinical trials and epidemiologic studies.
Calculating Dose Release Factors to Obtain the Worst-Case Maximally Exposed Location by Sector
The aim of this project was to update the SRS Dose Release Factors (DRF's) for the Maximally Exposed Individual (MEI) for 20 area release points onsite. To update, potential MEIs now include onsite locations and modeled stack heights were updated to match onsite operations. The DRF's and MEI locations are used to ensure DOE and EPA compliance is met for dose standards. The Environmental Protection Agency (EPA) requires the use of the computer model CAP88 to estimate doses for demonstrating compliance with 40 CFR 61, the National Emission Standard for Hazardous Air Pollutants (NESHAP). The location of the maximally exposed individual (MEI) by sector and distance is required for execution of CAP88. The worst-case sector is the sector and distance where an offsite individual would receive the highest dose due to a potential release from a designated release location at a facility. The worst-case sector analysis addresses potential ground-level and stack-height releases from 20 areas of Savannah River Site (SRS). Weather patterns were analyzed at each of these areas relative to sixteen compass points. The analysis makes use of recently updated distance data and meteorological data. The computer model, CAP88 is EPA's software system used by the Department of Energy (DOE) to calculate the receptor dose due to routine atmospheric releases via a gaussian plume at the Savannah River Site (SRS). The dose-release factors (DRFs) are used to estimate the offsite and onsite dose from facility-specific releases and represent the dose to a receptor exposed to 1 Ci of a specified radionuclide being released into the atmosphere. The DRFs are simply a ratio of the TED to the release rate and, therefore, are directly scalable. The DRF values listed in the Appendix can be applied to expected release values from each area to estimate the potential dose to an individual adult at each location. NESHAP DRFs have been supplied to Environmental Compliance and Area Closure Projects (EC and ACP) for many years and are periodically updated to include changes in Cap88. estimate the potential dose to an individual adult at each location DRF in mrem Ci{sup -1} are estimated by modeling the total effective dose (TED) in mrem yr{sup -1} assuming an annual atmospheric release rate of 1 Ci yr-1 of the associated radionuclides. TED = Effective Dose (ED) + Committed Effective Dose (CED). TED = DRF/RR. Approach and Methods: Determine possible MEI locations Onsite/Offsite including buildings and farms; Determine the distances from the release area to the possible MEI location and the direction from the release to the MEI location; Using the most recent meteorological data (2007-2011) and parameters, run CAP88 for each release area for each compass sector and previously calculated distances to MEI locations using a 1 Ci release rate for tritium; Use the calculated the air concentration values to determine the MEI for each sector from CAP88. The relationship between air concentration and received dose is directly proportional and can be used to determine which locations to calculate DRF's and a dose for an MEI; The DRFs are found for each compass sector from 20 SRS release areas using CAP88-PC Version 4.0; Each location is calculated with ground level releases evaluated for each area for a list of radionuclides, some with and some without progenies; Compare the DRFs of the potential onsite MEIs to offsite MEIs. Based on the 2018 MEI Report, the Site worst case sector MEI is located 593 mW of B-Area. This MEI location represents a point along the main road that travels through a tract of land leased to the SC National Guard. While this location is estimated to have the highest exposure, minimal radioactivity is released from B-Area. In 2017, SRS requested and was approved by the EPA to change the location for modeling site releases from the Center of Site to H-Area, and to use six stack heights. H-Area emission account for approximately 90% of all radioactive operations onsite. The MEI for H-Area was found to be 11,458 m NNE which locates the Savannah River Ecology Lab Conference Center. Comparisons for 2018 data and 2014 shows the new methods of calculation are more conservative yet still remain well below the DOE 100 mrem limit.
Learned magnetic map cues and two mechanisms of magnetoreception in turtles
Growing evidence indicates that migratory animals exploit the magnetic field of the Earth for navigation, both as a compass to determine direction and as a map to determine geographical position. It has long been proposed that, to navigate using a magnetic map, animals must learn the magnetic coordinates of the destination, yet the pivotal hypothesis that animals can learn magnetic signatures of geographical areas has, to our knowledge, yet to be tested. Here, in this work, we report that an iconic navigating species, the loggerhead turtle ( Caretta caretta ), can learn such information. When fed repeatedly in magnetic fields replicating those that exist in particular oceanic locations, juvenile turtles learned to distinguish magnetic fields in which they encountered food from magnetic fields that exist elsewhere, an ability that might underlie foraging site fidelity. Conditioned responses in this new magnetic map assay were unaffected by radiofrequency oscillating magnetic fields, a treatment expected to disrupt radical-pair-based chemical magnetoreception, suggesting that the magnetic map sense of the turtle does not rely on this mechanism. By contrast, orientation behaviour that required use of the magnetic compass was disrupted by radiofrequency oscillating magnetic fields. The findings provide evidence that two different mechanisms of magnetoreception underlie the magnetic map and magnetic compass in sea turtles.