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WASP is a NASA developed Fine Pointing System adaptable to a variety of Science Instruments. Standardized System with Reusable Parts to Minimize the Cost to Users and NASA. Supports Multiple Science Disciplines and a wide range of Masses and Inertias. Currently Operational and Available for Science Collaborations.
To the extent it makes sense, leverage JWST (James Webb Space Telescope) knowledge, designs, architectures. GSE (Ground Support Equipment) good starting point. Develop a full end-to-end architecture that closes. Try to avoid recreating the wheel except where needed. Optimize from there (mainly for stability and coronagraphy). Develop a scalable design reference mission (9.2 meters). Do just enough work to understand launch break points in aperture size Demonstrate 10 pm (phase modulation) stability is achievable on a design reference mission. A really key design driver is the most robust stability possible!!! Make design compatible with starshades. While segmented coronagraphs with high throughput and large bandpasses are important, make the system serviceable so you can evolve the instruments. Keep it room temperature to minimize the costs associated with cryo. Focus resources on the contrast problem. Start with the architecture and connect it to the technology needs.
A global, satellite-based, terrestrial snow mission planning tool is proposed to help inform experimental mission design with relevance to snow depth and snow water equivalent (SWE). The idea leverages the capabilities of NASAs Land Information System (LIS) and the Tradespace Analysis Tool for Constellations (TAT C) to harness the information content of Earth science mission data across a suite of hypothetical sensor designs, orbital configurations, data assimilation algorithms, and optimization and uncertainty techniques, including cost estimates and risk assessments of each hypothetical orbital configuration.One objective the proposed observing system simulation experiment (OSSE) is to assess the complementary or perhaps contradictory information content derived from the simultaneous collection of passive microwave (radiometer), active microwave (radar), and LIDAR observations from space-based platforms. The integrated system will enable a true end-to-end OSSE that can help quantify the value of observations based on their utility towards both scientific research and applications as well as to better guide future mission design. Science and mission planning questions addressed as part of this concept include:1. What observational records are needed (in space and time) to maximize terrestrial snow experimental utility?2. How might observations be coordinated (in space and time) to maximize utility? 3. What is the additional utility associated with an additional observation?4. How can future mission costs being minimized while ensuring Science requirements are fulfilled?
Global temperature is a fundamental climate metric highly correlated with sea level, which implies that keeping shorelines near their present location requires keeping global temperature within or close to its preindustrial Holocene range. However, global temperature excluding short-term variability now exceeds +1 C relative to the 1880 - 1920 mean and annual 2016 global temperature was almost +1.3 C. We show that global temperature has risen well out of the Holocene range and Earth is now as warm as it was during the prior (Eemian) interglacial period, when sea level reached 6 - 9 m higher than today. Further, Earth is out of energy balance with present atmospheric composition, implying that more warming is in the pipeline, and we show that the growth rate of greenhouse gas climate forcing has accelerated markedly in the past decade. The rapidity of ice sheet and sea level response to global temperature is difficult to predict, but is dependent on the magnitude of warming. Targets for limiting global warming thus, at minimum, should aim to avoid leaving global temperature at Eemian or higher levels for centuries. Such targets now require "negative emissions", i.e., extraction of CO2 from the air. If phasedown of fossil fuel emissions begins soon, improved agricultural and forestry practices, including reforestation and steps to improve soil fertility and increase its carbon content, may provide much of the necessary CO2 extraction. In that case, the magnitude and duration of global temperature excursion above the natural range of the current interglacial (Holocene) could be limited and irreversible climate impacts could be minimized. In contrast, continued high fossil fuel emissions today place a burden on young people to undertake massive technological CO2 extraction if they are to limit climate change and its consequences. Proposed methods of extraction such as bioenergy with carbon capture and storage (BECCS) or air capture of CO2 have minimal estimated costs of USD 89 - 535 trillion this century and also have large risks and uncertain feasibility. Continued high fossil fuel emissions unarguably sentences young people to either a massive, implausible cleanup or growing deleterious climate impacts or both.
A global, satellite-based, terrestrial snow mission planning tool is proposed to help inform experimental mission design with relevance to snow depth and snow water equivalent (SWE). The idea leverages the capabilities of NASA's Land Information System (LIS) and the Tradespace Analysis Tool for Constellations (TAT-C) to harness the information content of Earth science mission data across a suite of hypothetical sensor designs, orbital configurations, data assimilation algorithms, and optimization and uncertainty techniques, including cost estimates and risk assessments of each hypothetical permutation. One objective of the proposed observing system simulation experiment (OSSE) is to assess the complementary or perhaps contradictory information content derived from the simultaneous collection of passive microwave (radiometer), active microwave (radar), and LIDAR observations from space-based platforms. The integrated system will enable a true end-to-end OSSE that can help quantify the value of observations based on their utility towards both scientific research and applications as well as to better guide future mission design. Science and mission planning questions addressed as part of this concept include: What observational records are needed (in space and time) to maximize terrestrial snow experimental utility? How might observations be coordinated (in space and time) to maximize this utility? What is the additional utility associated with an additional observation? How can future mission costs be minimized while ensuring Science requirements are fulfilled?
The primary goal of this project has been to investigate if ground-based visible and near-infrared passive radiometers that have polarization sensitivity can determine the thermodynamic phase of overlying clouds, i.e. if they are comprised of liquid droplets or ice particles. While this knowledge is important by itself for our understanding of the global climate, it can also help improve cloud property retrieval algorithms that use total (unpolarized) radiance to determine Cloud Optical Depth (COD). This is a potentially unexploited capability of some instruments in the NASA Aerosol Robotic Network (AERONET), which, if practical, could expand the products of that global instrument network at minimal additional cost. We performed simulations that found, for zenith observations, cloud thermodynamic phase is often expressed in the sign of the Q component of the Stokes polarization vector. We chose our reference frame as the plane containing solar and observation vectors, so the sign of Q indicates the polarization direction, parallel (negative) or perpendicular (positive) to that plane. Since the quantity of polarization is inversely proportional to COD, optically thin clouds are most likely to create a signal greater than instrument noise. Besides COD and instrument accuracy, other important factors for the determination of cloud thermodynamic phase are the solar and observation geometry (scattering angles between 40 and 60 degrees are best), and the properties of ice particles (pristine particles may have halos or other features that make them difficult to distinguish from water droplets at specific scattering angles, while extreme ice crystal aspect ratios polarize more than compact particles). We tested the conclusions of our simulations using data from polarimetrically sensitive versions of the Cimel 318 sun photometerradiometer that comprise AERONET. Most algorithms that exploit Cimel polarized observations use the Degree of Linear Polarization (DoLP), not the individual Stokes vector elements (such as Q). For this reason, we had no information about the accuracy of Cimel observed Q and the potential for cloud phase determination. Indeed, comparisons to ceilometer observations with a single polarized spectral channel version of the Cimel at a site in the Netherlands showed little correlation. Comparisons to Lidar observations with a more recently developed, multi-wavelength polarized Cimel in Maryland, USA, show more promise. This divergence between simulations and observations has prompted us to begin the development of a small test instrument called the Sky Polarization Radiometric Instrument for Test and Evaluation (SPRITE). This instrument is specifically devoted to the accurate observation of Q, and the testing of calibration and uncertainty assessment techniques, with the ultimate goal of understanding the practical feasibility of these measurements.
The Mars Global Surveyor (MGS) mission, scheduled for launch in November 1996, will employ aerobraking as a means of reaching a low altitude, sun-synchronous mapping orbit. This technique is necessary to minimize the cost of the mission. The dry mass of the spacecraft and the launch vehicle capability do not permit an all-propulsive transfer to the desired orbit. Aerobraking concepts are discussed.
The basic questions addressed in this paper are how to avoid future surprise growth in Mission Operations and Data Analysis (MO&DA) costs, and how to minimize total MO&DA costs for planetary missions. The context of this paper and its conclusions is in the arena of JPL mission operations support. The fundamental conclusion is that there is no simple, single solution: the entire Project life-cycle must be addressed.
The control allocation problem was investigated for linear dynamical systems with known parametric uncertainty. Minimizing a cost function that penalizes the variance of the error in achieving commanded forces and moments on the vehicle resulted in a special case of the weighted pseudo-inverse allocator. Rather than an engineer designing the weighting matrix, it is computed from the covariances of the control effectiveness parameters. This minimum-variance allocator balances the effectiveness of the control inputs against the corresponding levels of uncertainty. The approach was demonstrated using simulations of aircraft with realistic uncertainty levels operating in open-loop and closed-loop configurations. Results showed that when model uncertainty is known, significant, and unevenly distributed amongst the controls, the minimum-variance allocator more often achieves the intended forces and moments on the vehicle in comparison to other allocators, which can lead to increased performance, reliability, and safety during flight tests. The cost for this robustness is a diminished achievable moment space for the vehicle.
Global lightning detection has advanced greatly over the past few decades both on ground and from orbit. Ground-based systems like the Lightning Mapping Array (LMA) excel at high-precision 3D reconstruction of local flashes, while spaceborne lightning sensors have much larger potential coverage but have been limited by coarser resolution and often rely on data from other instruments to determine flash location. The primary focus of this study is to examine the level of flash detail that can be expected from one or more low-Earth orbiting small satellites that combine VHF and optical measurements of lightning, which is a new mission concept called CubeSpark. The goal of CubeSpark is to map the 3D charge structure of thunderstorms at 1-2 km spatial resolution on a global scale, enabling a host of new atmospheric and space electricity studies. In order to maximize the potential data quality and minimize potential cost, flashes were simulated beneath single- and multi-satellite configurations. In the multi-satellite approach, RF detectors on each of the six satellites would measure the arrival times of impulsive VHF sources to collectively pinpoint their locations in 3D and reconstruct flashes with higher resolution than has been achieved from space. A single-station approach for 3D observation of lightning would follow the method of determining altitudes of strong VHF sources that produce trans-ionospheric pulse pairs (TIPPs) while relying on an on-board high-resolution optical day/night lightning mapper for approximate horizontal flash locations. Here we present preliminary results comparing the expected data fidelity and accuracy between these methods to inform potential satellite missions like CubeSpark.
This training exercise provides users with an introduction to and hands-on, interactive exploration of REopt Lite's capabilities. REopt Lite is a free, publicly available techno-economic optimization web tool for distributed energy systems, developed at the National Renewable Energy Laboratory (NREL). REopt Lite helps organizations evaluate the economic viability of grid-connected solar photovoltaics (PV), wind turbines, and battery storage; identify system sizes and battery dispatch strategies to minimize energy costs; and estimate how long a system can sustain critical load during a grid outage. The model is formulated as a mixed-integer linear program based in an underlying application programming interface (API) that is also free and publicly available. This training activity is structured as a group exercise. Participants split into eight groups and each group is assigned a different hypothetical site to model and assess the opportunity for solar PV + battery storage. Groups work together to develop results for their site and then re-convene to compare and discuss results, inputs/drivers of the analysis, and other factors impacting the decision-making process for behind-the-meter solar PV and battery storage.
Recent advancements within smart neighborhoods where utilities are enabling automatic control of appliances such as heating, ventilation, and air conditioning (HVAC) and water heater (WH) systems are providing new opportunities to minimize energy costs through reduced peak load. This requires systematic collection, storage, management, and in-memory processing of large volumes of streaming data for fast performance. In this paper, we propose a multi-tier layered IoT software framework that enables effective descriptive and predictive data analysis for understanding live operation of the neighborhood, fault identification, and future opportunities for further optimization of load curves. We then demonstrate how we achieve live situational awareness of the connected neighborhood through a suite of visualization components. Finally, we discuss a few analytic dashboards that address questions such as peak load reductions obtained due to optimization, customer preference for automatic control of appliances (do they override the automatic control of HVAC?, etc.). 1 1 This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
While there are many advantages to electric public transit vehicles, they also pose new challenges for fleet operators. One key challenge is defining a charge scheduling policy that minimizes operating costs and power grid disruptions while maintaining schedule adherence. An uncoordinated policy could result in some buses running out of charge before completing their trip, while a grid agnostic policy might incur higher energy costs or cause an adverse impact on the grid’s distribution system. We present a grid aware decision-theoretic framework for electric bus charge scheduling that accounts for energy price, grid load, and bus status. The framework connects environmental models for traffic (SUMO) and the electric grid (GridLAB-D) to a planner, which evaluates bus charging decisions with regard to their long-term effect on grid reliability and cost. The framework has been evaluated on a simulation of Richland, WA’s bus and grid network, and compared to greedy methods.
Radiation signature training device sources are a continuation of a previous effort to produce a highly enriched uranium equivalent sphere. The original research was designed and motivated to produce a Department of Transportation special form source that emulated the passive gamma signature of a solid metal highly enriched uranium sphere. In addition, the mass reduction (i.e., of the 235 U) minimized logistical costs (security, criticality safety, radiological safety and transportation requirements). Radiation signature training device sources expand on the original concept, redesigning the encapsulation in a modular fashion that allows a variety of loadings. The result is a reconfigurable special nuclear material source set that can vary greatly in the magnitude of the gamma flux and the isotopic distribution. Use of the source to test a variety of standards (N42.34-2015, N42.38-2015, N42.43-2015, N42.53-2018, N42.48-2018, DHS-TCS Backpack Based Radiation Detection Systems, DHS-TCS Handheld Instruments Used for the Detection and Identification of Radionuclides, DHS-TCS Vehicle Mounted Mobile Systems) will be discussed.
A methodology is proposed for the improvement of electric distribution system resilience to high-impact, low-probability catastrophic events. An approach for dynamic network reconfiguration and coordination of distributed energy resources is introduced to assist in restoration efforts. The problem is formulated as a mixed-integer linear program that minimizes generation costs, the cost of lost load, and costs associated with equitable load shedding, while respecting operational limits of generation, loads, and the network. Constraints are imposed on binary switching variables to ensure equitable load shedding in emergency situations. Numerical validation of the proposed approach is conducted on an example distribution feeder, and case studies are performed to analyze the impact of various parameters in the optimization problem formulation.
Certain embodiments of the present invention are configured to facilitate analyzing computer code more efficiently. For example, by conducting a first level abstraction (e.g., symbolic interpretation and algebraic simplification) and a second level abstraction (e.g., generalization) of the computer code, the analysis may more accurately account for variations in the code that may occur as a result of register renaming, instruction reordering, choice of instructions, etc. while minimizing the cost of computations required to perform the analysis.
This work describes a one-dimensional model of a water-cooled printed circuit heat exchanger (PCHE) condensing supercritical CO2. The model is developed for use in cycle optimization studies (e.g., minimizing levelized cost of electricity) as either the main heat rejection cooler and/or a compressor intercooler for recompression closed Brayton supercritical CO2 power cycles. Sensitivity and case studies are used to illustrate the impact of important model parameters, and this includes allowing for independent variation of zig-zag channel wave angles on the CO2 and water side. Results show that for a given CO2 design pressure (and thus saturation temperature), the PCHE design inlet water temperature has a significant impact on the PCHE size. Results also demonstrate that if wave angles are the same on the CO2 and water side, the water side pressure drop will have more influence on determining the optimum PCHE mass than the CO2 side pressure drop. Reducing the water side wave angle to near straight channel flow offers a more compact design for a similar water side pressure drop (and pump power requirement). Cases are also shown for further increasing the compactness and how the PCHE mass is affected along with water pump power.
Hybrid additive featured plates used to form an overall microchannel heat exchanger and corresponding method of manufacture are disclosed. Various additive manufacturing (AM) techniques may be used to form walls defining microchannel features on a plate substrate. The manufacturing method is a hybrid process in that leverages both additive and conventional manufacturing techniques to minimize both cost and fabrication time.