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At least 199 records · Page 11

Streamlining Ground Station Network Compatibility Test for Small Satellites

A team of eight subject matter experts at NASA Goddard Space Flight Center (GSFC) completed a Lean Six Sigma project to identify process improvements for the compatibility test process for small satellites planning to use the NASA Near Earth Network (NEN). Ground station network compatibility testing is designed to reduce the risk to missions by resolving issues between the spacecraft's flight communication and navigation components and the ground systems prior to launch. Compatibility testing, which consists of a series of tests performed over a period of months and documented in reports, is an important step meant to prevent post-launch anomalies that could lead to expensive troubleshooting or mission failure. Compared to traditional missions, small satellite missions typically have a smaller budget and compressed schedules, which can result in small satellite projects' willingness to accept the risk associated with less comprehensive compatibility testing. Optimization and or refinement of the compatibility test process for small satellite missions could alleviate some of the pressures inherent with these factors. The goal of the Lean Six Sigma project was to develop alternative scalable methods of compatibility testing for small satellites. The Lean Six Sigma approach and the results of the project are reviewed in this paper.

Streamlining↗

PDPTW-DB: MILP-Based Offline Route Planning for PDPTW with Driver Breaks

The Pickup and Delivery Problem with Time Windows (PDPTW) involves optimizing routes for vehicles to meet pickup and delivery requests within specific time constraints, a challenge commonly faced in logistics and transportation. Microtransit, a flexible and demand-responsive service using smaller vehicles within defined zones, can be effectively modeled as a PDPTW. Yet, the need for driver breaks—a key human constraint—is frequently overlooked in PDPTW solutions, despite being necessary for regulatory compliance. This study presents a novel mixed-integer linear programming formulation for the Pickup and Delivery Problem with Time Windows and Driver Breaks (PDPTW-DB). To the best of our knowledge this formulation is the first to consider mandatory periodic driver breaks within optimized Microtransit routes. The proposed model incorporates regulatory compliant break scheduling directly within the vehicle routing optimization framework. By considering driver break requirements as an integral component of the optimization process, rather than as a post-processing step, the model enables the generation of routes that respect hours of service regulations while minimizing operational costs. This integrated approach facilitates the generation of schedules that are operationally efficient and prioritize driver welfare through driver breaks. We work with a public transit agency from the southern USA, and highlight the specific nuances of driver break optimization, and present a Pickup and Delivery Problem with Time Windows formulation for optimizing Microtransit operations and scheduling driver breaks. We validate our approach using real-world data from the transit agency. Our results validate our formulation in producing cost-effective, and regulation-compliant solutions.

Applied Computing, Transportation↗

Applying Squeaky-Wheel Optimization Schedule Airborne Astronomy Observations

We apply the Squeaky Wheel Optimization (SWO) algorithm to the problem of scheduling astronomy observations for the Stratospheric Observatory for Infrared Astronomy, an airborne observatory. The problem contains complex constraints relating the feasibility of an astronomical observation to the position and time at which the observation begins, telescope elevation limits, special use airspace, and available fuel. Solving the problem requires making discrete choices (e.g. selection and sequencing of observations) and continuous ones (e.g. takeoff time and setting up observations by repositioning the aircraft). The problem also includes optimization criteria such as maximizing observing time while simultaneously minimizing total flight time. Previous approaches to the problem fail to scale when accounting for all constraints. We describe how to customize SWO to solve this problem, and show that it finds better flight plans, often with less computation time, than previous approaches.

Frank, Jeremy↗

Framework for Architecture Trade Study Using MBSE and Performance Simulation

Increasing complexity in modern systems as well as cost and schedule constraints require a new paradigm of system engineering to fulfill stakeholder needs. Challenges facing efficient trade studies include poor tool interoperability, lack of simulation coordination (design parameters) and requirements flowdown. A recent trend toward Model Based System Engineering (MBSE) includes flexible architecture definition, program documentation, requirements traceability and system engineering reuse. As a new domain MBSE still lacks governing standards and commonly accepted frameworks. This paper proposes a framework for efficient architecture definition using MBSE in conjunction with Domain Specific simulation to evaluate trade studies. A general framework is provided followed with a specific example including a method for designing a trade study, defining candidate architectures, planning simulations to fulfill requirements and finally a weighted decision analysis to optimize system objectives.

Ryan, Jessica↗

Reducing Stray Light To Characterize Nirspec Subsystems: The Focal Plane Array And Micro-Shutter Array

The James Webb Space Telescope (JWST) is an infrared, space-based telescope scheduled for launch in 2013. JWST includes four scientific instruments, including the Near Infrared Spectrometer (NIRSpec), which operates in the wavelength range from 0.6 to 5 microns. NASA/Goddard Space Flight Center (GSFC) is responsible for two NIRSpec subsystems: the detector subsystem, with its focal plane array (FPA), and the micro-shutter subsystem, with its micro-shutter array (MSA). The FPA is comprised of two side-by-side Rockwell Scientific HgCdTe 2kx2k detectors, with detectors and readout electronics optimized for low noise. The MSA is a GSFC developed micro-electro-mechanical system (MEMS) that serves as a programmable slit mask, allowing NIRSpec to obtain simultaneous spectra of >100 objects in a single field of view. We present the optical characterization test plan of the FPA. The test plan is driven by many requirements: cryogenic operating temperature, a flight-like beam shape, and multi-wavelength photon flux from 1 to 60,000 per second, thus low stray light is critical. We use commercial optical modeling software to predict stray light effects at the FPA. We also present the optical contrast test plan of the MSA. Since each individual shutter element operates in on/off fashion, the most important optical metric is contrast. The MSA structure is designed to minimize stray and scattered light, and the test setup reduces stray light such that the optical contrast requirement is met.

Connelly, Joseph A.↗

Benefits Assessment for Single-Airport Tactical Runway Configuration Management Tool (TRCM)

The System-Oriented Runway Management (SORM) concept was developed as part of the Airspace Systems Program (ASP) Concepts and Technology Development (CTD) Project, and is composed of two basic capabilities: Runway Configuration Management (RCM), and Combined Arrival/Departure Runway Scheduling (CADRS). RCM is the process of designating active runways, monitoring the active runway configuration for suitability given existing factors, and predicting future configuration changes; CADRS is the process of distributing arrivals and departures across active runways based on local airport and National Airspace System (NAS) goals. The central component in the SORM concept is a tool for taking into account all the various factors and producing a recommendation for what would be the optimal runway configuration, runway use strategy, and aircraft sequence, considering as many of the relevant factors required in making this type of decision, and user preferences, if feasible. Three separate tools were initially envisioned for this research area, corresponding to the time scale in which they would operate: Strategic RCM (SRCM), with a planning horizon on the order of several hours, Tactical RCM (TRCM), with a planning horizon on the order of 90 minutes, and CADRS, with a planning horizon on the order of 15-30 minutes[1]. Algorithm development was initiated in all three of these areas, but the most fully developed to date is the TRCM algorithm. Earlier studies took a high-level approach to benefits, estimating aggregate benefits across most of the major airports in the National Airspace Systems (NAS), for both RCM and CADRS [2]. Other studies estimated the benefit of RCM and CADRS using various methods of re-sequencing arrivals to reduce delays3,4, or better balancing of arrival fixes5,6. Additional studies looked at different methods for performing the optimization involved in selecting the best Runway Configuration Plan (RCP) to use7-10. Most of these previous studies were high-level or generic in nature (not focusing on specific airports), and benefits were aggregated for the entire NAS, with relatively low fidelity simulation of SORM functions and aircraft trajectories. For SORM research, a more detailed benefits assessment of RCM and CADRS for specific airports or metroplexes is needed.

Oseguera-Lohr, Rosa↗

Towards a Decision Support System for Space Flight Operations

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the three increments of this vision. These increments include (1) hardware and software system components and interfaces with the NASA ground system, (2) uncertainty management and (3) re-planning and automated execution. Each of these increments provide value independently; but some may also enable building of a subsequent increment.

Meshkat, Leila↗

Approximation algorithms for planning and control

A control system operating in a complex environment will encounter a variety of different situations, with varying amounts of time available to respond to critical events. Ideally, such a control system will do the best possible with the time available. In other words, its responses should approximate those that would result from having unlimited time for computation, where the degree of the approximation depends on the amount of time it actually has. There exist approximation algorithms for a wide variety of problems. Unfortunately, the solution to any reasonably complex control problem will require solving several computationally intensive problems. Algorithms for successive approximation are a subclass of the class of anytime algorithms, algorithms that return answers for any amount of computation time, where the answers improve as more time is allotted. An architecture is described for allocating computation time to a set of anytime algorithms, based on expectations regarding the value of the answers they return. The architecture described is quite general, producing optimal schedules for a set of algorithms under widely varying conditions.

Boddy, Mark↗

Integrated Traffic Flow Management Decision Making

A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

Grabbe, Shon R.↗

Towards a decision support system for space flight operations

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The differences between the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the four increments of this vision. These increments include (1) the existing capabilities (2) hardware and software system components and interfaces with the NASA ground system, (3) uncertainty management and (4) re-planning and automated execution. Each of these increments provides value independently; but some may also enable building of a subsequent increment.

Ruszkowski, James↗

DEPLOYING FAST CHARGING INFRASTRUCTURE FOR ELECTRIC VEHICLES IN URBAN NETWORKS: AN ACTIVITY-BASED APPROACH

This paper explores an important problem under the domain of network modeling, the optimal configuration of charging infrastructure for electric vehicles (EVs) in urban networks considering EV users' daily activities and charging behavior. This study proposes a charging behavior simulation model considering different initial state of charge (SOC), travel distance, availability of home chargers, and the daily schedule of trips for each traveler. The proposed charging behavior simulation model examines the complete chain of trips for EV users as well as the interdependency of trips traveled by each driver. The problem of finding the optimum charging configuration is then formulated as a mixed-integer nonlinear programming problem that considers the dynamics of travel time and travel distance, the interdependency of trips made by each driver, limited range of EVs, remaining battery capacity for recharging, waiting time in queue, and detour to access a charging station. This problem is solved using a metaheuristic approach for a large-scale case network. A series of examples are presented to demonstrate the model efficacy and explore the impact of energy consumption on the final SOC and the optimum charging infrastructure.

Chain of Trips↗

An interactive computer approach to performing resource analysis for a multi-resource/multi-project problem

New planning techniques and supporting computer tools are needed for the optimization of resources and costs for space transportation and payload systems. Heavy emphasis on cost effective utilization of resources has caused NASA program planners to look at the impact of various independent variables that affect procurement buying. A description is presented of a category of resource planning which deals with Spacelab inventory procurement analysis. Spacelab is a joint payload project between NASA and the European Space Agency and will be flown aboard the Space Shuttle starting in 1980. In order to respond rapidly to the various procurement planning exercises, a system was built that could perform resource analysis in a quick and efficient manner. This system is known as the Interactive Resource Utilization Program (IRUP). Attention is given to aspects of problem definition, an IRUP system description, questions of data base entry, the approach used for project scheduling, and problems of resource allocation.

Schlagheck, R. A.↗

Scheduling Mission Reconfiguration for an Interferometry Synthetic Aperture Radar Using Deep Reinforcement Learning

This paper presents a method to intelligently adapt the baseline of a synthetic aperture radar based on Deep Rein- forcement Learning to help create plans for missions that use formation flight for Earth observation purposes. The main contribution of this paper is the initial results we have found from applying the tool to a toy mission: measuring the ver- tical structure of forests by using a synthetic aperture radar mounted on a formation of 7 satellites orbiting the Earth in a Sun Synchronous Orbit. We have found that with a reward function based on expected science return over time and fuel usage, the Deep Reinforcement Learning planner is able to create plans with positive scientific returns while minimizing fuel usage. We also find that fuel usage and collision avoid- ance planning is better done with traditional methods, as Deep Reinforcement Learning does not converge to optimal solutions.

Viros-i-Martin, Antoni↗

EVA Swab Kit: Tools and Techniques for Collecting Aseptic Samples from Crewed Space Missions

Introduction: When we send humans to search for life on other planets, we'll need to know what we brought with us versus what may already be there. To ensure our crewed spacecraft meet planetary protection requirements—and to protect our science from human contamination—we'll need to assess and verify whether micro-organisms may be leaking/venting from our spacesuits. This requires collecting samples under Extravehicular Activity (EVA) conditions. Detailed, systematic research on forward contamination from robotic spacecraft has been steadily progressing since the Viking missions, but systematic studies of contamination from space suits has not been conducted in many years. The modern EMU (Extravehicular Mobility Unit) suit used by NASA is designed to leak at rates as high as 100 cc/min. Before humans land on Mars there is a critical need to understand the types and quantities of microbes that could be introduced via space suits. The Human Forward Contamination Assessment team at NASA’s Johnson Space Center (JSC) has developed a prototype EVA swab tool [1,2,3,4] designed for use in space to sample cleaned and uncleaned space suits to determine the present day microbial load and eventually the rate of leakage. The ability to assess microbial leakage early in advanced space suit and life support system design cycles will help avoid costly hardware redesign later. Test Objectives: The primary objective of EMU testing was to characterize the type of micro-organisms typically found on or near selected suit pressure joints under suit differential pressure conditions. Most human-borne microbes can fit through a 0.5 to 1.0 µm gap. Knowing which joints are more likely to leak will inform hardware design decisions. Knowing which types of micro-organisms may leak from EVA suits provides a basis for subsequent studies to characterize the viability of those organisms under destination conditions, as well as how far they might spread through natural or human-influenced processes. That data, in turn, will inform exploration mission operations and hardware design. The secondary objective of testing was to evaluate the interface between a fully suited test subject and the EVA swab tool at vacuum. Bulky EVA suits can restrict movement and limit visibility through the helmet visor. Fully suited testing is important for identifying tool design issues prior to flight. At exploration destinations, such as Mars, suited crew may be required to periodically sample their suits as part of an environmental monitoring protocol. Suit Microbial Sampling Results: This report details results of microbial swabs collected from current flight suit configurations worn by crew members assigned to upcoming ISS expedition missions as well as swabs collected from prototype suits intended for use on the Orion spacecraft. These tests were intended to characterize the types of contaminants found on flight suits under current, typical handling conditions. No attempt was made to change suit handling procedures, provide additional sterilization, or to limit typical potential contaminant sources. Using culture based techniques, we cultivated 235 CFU (colony forming units) comprised of 26 bacterial species and one fungal species on the outside of the suits. The fungal species and 14 of the bacterial species were unique to the suit surfaces and were not detected in any of the background samples collected within the chambers. We sequenced 755,434 ribosomal fragments on all of the suit surfaces from swab samples. 557,016 of these sequences represent DNA that survived at least 4 hours at vacuum. These sequences formed 2,464 OTU's (Operational Taxonomic Units, 97% similarity) showing low diversity in the samples. The most abundant sequences that survived vacuum belong to the genera Staphyloccocus, Ralstona, Bacillus and Rhodobacter all of which are common to the human microbiome. [5] See Danko et al., (2021) for more complete details of these first analyses. Further analysis of EVA suit materials with respect to the efficacy of various cleaning protocols and engineered containment solutions is planned to inform suit design for NASA’s Artemis Moon to Mars program crew testing. Swab Tool Function Results: The kit was demonstrated for fit and function in suited subject vacuum tests to determine how well the tool worked as an aseptic microbial sampling device as well as to identify any design elements that could be upgraded for EVA task specific improvement. It was found that sample acquisition efficacy could be enhanced by redesign of the sample canister to end-effector interface. Several modifications of the sample caddy assemblies to optimize EVA safety and functionality were also identified. Consequently, fabrication of the redesigned sample canister to end-effector assembly interfaces and and the sample caddy assemblies are required. Fabrication of sixteen flight sample canister assemblies (8 per each of two EVA Swab Kits) and two sample caddy assemblies are in process to be followed by hardware testing and certification to produce two flight-certified EVA Swab Kits for transport to ISS no earlier than summer of 2022. Sampling Strategy: The International Space Station is an ideal testbed for systematic studies of contamination from crewed vehicles since it has been continuously occupied for 20 years and exposed to non-terrestrial conditions. We will sample the exterior of the ISS during EVA using a purpose-built swab tool capable of maintaining sterility while undergoing temperature changes from -151 to +121°C under hard vacuum. Prior to each EVA, the project team will work with ISS mission managers to identify precise sampling locations, which will vary by EVA based on the translation paths and worksites scheduled for that particular EVA. Ideally, translation path handrails and areas near ECLSS (Environmental Control and Life Support System) external vent openings on a spacecraft would be assessed. There are currently more than a dozen ECLSS external vents on the ISS. Some are connected to systems that vent waste products, while others are intended to equalize cabin pressure. As EVA opportunity allows, microbial samples from any of these external vents would provide a valuable data point, though some will be more useful than others. Four criteria have been identified to help prioritize sampling sites near vents: • EVA Accessibility: To minimize cost, it is desired to piggy-back onto a planned EVA. Therefore, the sampling location must be readily accessible by an EVA crew • Type of Vented Products: Vent products that have been in direct contact with crew, such as cabin air, are more likely to contain microorganisms than vent products associated with isolated systems, such as experiment module combustion products. • Mass of Vented Products: Higher-flow vents are more likely to contain detectible levels of microbial contaminants than lower-flow vents. • Local Environment: Sample locations with relatively benign local conditions, such as warm surfaces shielded from direct ultraviolet (UV) radiation exposure, may be more likely to support microbial growth than locations with harsher local environmental conditions. Because EVA accessibility is the most important criteria, the proposal team worked with an astronaut and flight controllers using the Dynamic Onboard Ubiquitous Graphics (DOUG) tool. The DOUG virtual environment allows an operator to “fly” around the current ISS vehicle configuration to assess EVA translation paths, attach points, and keep-out zones. While analysis on station or rapid return to Earth would be preferable, samples collected from the exterior of the ISS have already been exposed to temperature variations between -157 and +121 °C as well as hard vacuum. Therefore, they should be fairly stable and robust. We hypothesize that samples collected from the ISS exterior could be stored for up to 6 months at -80°C without degradation. Sample canisters will be returned to Earth while frozen at -80°C for analysis, and sterilized canisters can be re-flown back to ISS to support additional sampling opportunities Relevance to NASA Exploration Objectives: These data will allow us to identify new or improved methods, technologies, and procedures for spacecraft sterilization and leakage mitigation to minimize the amount of contamination introduced to the environment by human explorers. This work is funded by NASA research grant: NNH18ZDA001N-PPR References: [1] Bell, M.S. et al. (2015) LPS XLVI, Abst. #1832 [2] Rucker et al. (2018) 42nd COSPAR (PPP.3) [3] Bell, M.S. et al. (2019) Mars Extant Life Conference, Abst. #5096.[4] Bell, M.S. et al., (2020) 43rd COSPAR (BO.2).[5] Danko D, et.al.,(2021)Front.Microbiol.12:608478.

Mary Suzanne Bell↗

Continuation of the University of Michigan Sounding Rocket Program

This interim report gives the activity on this grant through 31 October 1998, and the planned activities for the next fiscal year. A Project Initiation Conference (PIC) was held at the Wallops Flight Facility (WFF), with planning for the launch of flight 36.174 in Fall 1998. However, following the PIC, the WFF personnel decided that the experiment telemetry system had to be completely rewired, which required substantial design and wiring changes on the experiment side of the payload. These costs had not been anticipated in the FY98 budget, and used up considerable resources of the experimenters. In addition, the telemetry re-design was not completed until Fall 1998, so that there was no opportunity for a launch in 1998 (the Jupiter window closes in late November 1998 and it will reopen in late summer 1999). A Design Review was held by telecon with WFF personnel on 26 October 1998, with plans for the 36.174 launch now in late August 1999 with a launch window which extends into winter 2000. On a more positive note, we have been developing a vacuum UV calibration chamber in Michigan's Space Physics Research Lab, for future measurements of our experiment components, and this facility is now undergoing initial measurements of various calibration lamps in preparation for testing of the telescope UV reflective efficiency. This facility will greatly increase our ability to optimize our experiment for UV efficiency, which has been lacking in the past, and it will be made available for support of other NASA missions at Michigan and for visitors from other institutions. For the next flight 36.174, the following activities will be accomplished: (1) prepare the experiment, including replacement and upgrading of critical components, at University of Michigan; (2) pre-integrate the payload at the Wallops Flight Facility; (3) perform final far-UV calibration of instrument (4) perform final alignment, integration, and electrical checks at WSMR; (5) launch payload from WSMR and check condition of recovered payload; (6) perform post-flight calibration, if necessary and applicable (7) reduce and analyze flight data. The following pages contain information from the experimenter package for the Design Review for the next flight, 36.174, listing the plans, changes, and schedule for this flight.

Clarke, John↗

Improvements to Integrated Tradespace Analysis of Communications Architectures (ITACA) Network Loading Analysis Tool

NASA's SCENIC project aims to simplify and reduce the cost of space mission planning by replicating the analysis capabilities of commercially licensed software which are integrated with relevant analysis parameters specific to SCaN assets and SCaN supported user missions. SCENIC differs from current tools that perform similar analyses in that it 1) does not require any licensing fees, 2) will provide an all-in-one package for various analysis capabilities that normally requires add-ons or multiple tools to complete. As part of SCENIC's capabilities, the ITACA network loading analysis tool will be responsible for assessing the loading on a given network architecture and generating a network service schedule. ITACA will allow users to evaluate the quality of service of a given network architecture and determine whether or not the architecture will satisfy the mission's requirements. ITACA is currently under development, and the following improvements were made during the fall of 2017: optimization of runtime, augmentation of network asset pre-service configuration time, augmentation of Brent's method of root finding, augmentation of network asset FOV restrictions, augmentation of mission lifetimes, and the integration of a SCaN link budget calculation tool. The improvements resulted in (a) 25% reduction in runtime, (b) more accurate contact window predictions when compared to STK(Registered Trademark) contact window predictions, and (c) increased fidelity through the use of specific SCaN asset parameters.

analysis↗

HyTES: Thermal Imaging Spectrometer Development

The Jet Propulsion Laboratory has developed the Hyperspectral Thermal Emission Spectrometer (HyTES). It is an airborne pushbroom imaging spectrometer based on the Dyson optical configuration. First low altitude test flights are scheduled for later this year. HyTES uses a compact 7.5-12 micrometer m hyperspectral grating spectrometer in combination with a Quantum Well Infrared Photodetector (QWIP) and grating based spectrometer. The Dyson design allows for a very compact and optically fast system (F/1.6). Cooling requirements are minimized due to the single monolithic prism-like grating design. The configuration has the potential to be the optimal science-grade imaging spectroscopy solution for high altitude, lighter-than-air (HAA, LTA) vehicles and unmanned aerial vehicles (UAV) due to its small form factor and relatively low power requirements. The QWIP sensor allows for optimum spatial and spectral uniformity and provides adequate responsivity which allows for near 100mK noise equivalent temperature difference (NEDT) operation across the LWIR passband. The QWIP's repeatability and uniformity will be helpful for data integrity since currently an onboard calibrator is not planned. A calibration will be done before and after eight hour flights to gage any inconsistencies. This has been demonstrated with lab testing. Further test results show adequate NEDT, linearity as well as applicable earth science emissivity target results (Silicates, water) measured in direct sunlight.

remote sensing↗

Calculation of Operations Efficiency Factors for Mars Surface Missions

For planning of Mars surface missions, to be operated on a sol-by-sol basis by a team on Earth (where a "sol" is a Martian day), activities are described in terms of "sol types" that are strung together to build a surface mission scenario. Some sol types require ground decisions based on a previous sol's results to feed into the activity planning ("ground in the loop"), while others do not. Due to the differences in duration between Earth days and Mars sols, for a given Mars local solar time, the corresponding Earth time "walks" relative to the corresponding times on the prior sol/day. In particular, even if a communication window has a fixed Mars local solar time, the Earth time for that window will be approximately 40 minutes later each succeeding day. Further complexity is added for non-Mars synchronous communication relay assets, and when there are multiple control centers in different Earth time zones. The solution is the development of "ops efficiency factors" that reflect the efficiency of a given operations configuration (how many and location of control centers, types of communication windows, synchronous or non-synchronous nature of relay assets, sol types, more-or-less sustainable operations schedule choices) against a theoretical "optimal" operations configuration for the mission being studied. These factors are then incorporated into scenario models in order to determine the surface duration (and therefore minimum spacecraft surface lifetime) required to fulfill scenario objectives. The resulting model is used to perform "what-if" analyses for variations in scenario objectives. The ops efficiency factor is the ratio of the figure of merit for a given operations factor to the figure of merit for the theoretical optimal configuration. The current implementation is a pair of models in Excel. The first represents a ground operations schedule for 500 sols in each operations configuration for the mission being studied (500 sols was chosen as being a long enough time to capture variations in relay asset interactions, Earth/Mars time phasing, and seasonal variations in holidays). This model is used to estimate the ops efficiency factor for each operations configuration. The second model in a separate Excel spreadsheet is a scenario model, which uses the sol types to rack up the total number of "scenario sols" for that scenario (in other words, the ideal number of sols it would take to perform the scenario objectives). Then, the number of sols requiring ground in the loop is calculated based on the soil types contained in the given scenario. Next, the scenario contains a description of what sequence of operations configurations is used, for how many days each, and this is used with the corresponding ops efficiency factors for each configuration to calculate the "ops duration" corresponding to that scenario. Finally, a margin is applied to determine the minimum surface lifetime required for that scenario. Typically, this level of analysis has not been performed until much later in the mission, and has not been able to influence mission design. Further, the notion of moving to sustainable operations during Prime Mission - and the effect that that move would have on surface mission productivity and mission objective choices - has not been encountered until the most recent rover missions (MSL and Mars 2018).

Layback, Sharon L.↗