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The Lunar Soil Particle Separator (LSPS) beneficiates soil prior to in situ resource utilization (ISRU). It can improve ISRU oxygen yield by boosting the concentration of ilmenite, or other iron-oxide-bearing materials found in lunar soils, which can substantially reduce hydrogen reduction reactor size, as well as drastically decreasing the power input required for soil heating
Early in the development of the Crew Health Care System (CHECS) for the International Space Station (ISS), it was recognized that detection of target volatile organic compounds would be a key component of the air monitoring strategy. Experiences during the NASA/Mir program supported the decision to include a real-time volatile organic analyzer (VOA) aboard ISS to help assess the impact of air quality events on crew health and determine the effectiveness of decontamination efforts. Toward this end, a joint development by the Toxicology Laboratory at Johnson Space Center and Graseby Dynamics produced a VOA that has been delivered and is ready for the first 5 years of ISS operation. The first-generation VOA selection criteria included minimizing size, weight, and power consumption while maintaining analytical performance. Measuring available technologies against these criteria, a VOA system based upon gas chromatography/ion mobility spectrometry (GC/IMS) was selected in the mid-90's. However, as NASA looks forward to later-stage ISS operations and to new frontiers such as human exploration of Mars, the ISS VOA (weighing 43 kg and consuming 160 watts) must be replaced by a smaller, less resource-intensive device. This paper will present a possible second-gene ration VOA based upon the same technology as the first-generation unit. Utilizing GC/IMS technology again will permit the instrumental data and experience gained during the initial phase of ISS to be applied to later ISS phases and advanced spacecraft missions. During the past 3 years, efforts to reduce the size of ion mobility spectrometers have been pursued by Graseby Dynamics, the manufacturer of the first-generation VOA. The concept of operation, expected analytical performance, and estimated size of a fully functional second-generation VOA based upon GC/mini-IMS technology will be presented. Furthermore, results of initial laboratory evaluations will be shown.
Matrix organizations allow scientific facilities to share specialized personnel across projects, operations, maintenance, and strategic initiatives. Nominal staffing allocations, however, may not capture the schedule consequences of fragmented individual commitments, limited access to specialist groups, and intermittent availability of key decision makers. We developed a stochas- tic, daily-time-step simulation of a hypothetical medium-sized accelerator-facility project com- prising sequential phases and parallel tasks. Each task requires role-specific work measured in FTE-days. Ordinary personnel may be unavailable because they contribute concurrently to other institutional activities, while designated key roles have independently specified daily un- availability probabilities. An organization-wide priority factor scales the number of people from each functional group who can effectively contribute to the project. It is interpreted as a composite proxy for project access and workforce fragmentation across competing commit- ments. We examined project completion time as a function of this factor and Project Lead unavailability using 100 Monte Carlo runs per condition. Increasing priority factor from 0.1 to 1.0 reduced median completion time from 1708.5 days (interquartile range 1681.5–1735.25) to 390 days (interquartile range 379–399). At priority factor = 0.1, increasing Project Lead unavailability from 0.5 to 0.9 increased median completion time from 1713.5 days (interquartile range 1691–1733.25) to 4,417 days (interquartile range 4271.75–4550.5). The model quantifies the commonly expected sensitivity of project schedules to fragmented resource commitments and limited coordination availability. Within this model, the results also indicate a possible threshold regime in which small increases in workforce availability yield only modest sched- ule improvements until sufficient capacity becomes accessible, after which project performance improves sharply. With further validation and calibration, this quantitative framework could support resource-allocation decisions during initial project planning and subsequent schedule rebaselining.
Here we present a quantum algorithm for implementing φ 4 lattice scalar field theory on qubit computers. The field is represented in the discretized field amplitude basis. The number of qubits and elementary gates required by the implementation of the evolution operator is proportional to the lattice size. The algorithm allows efficient φ 4 state preparation for a large range of input parameters in both the normal and broken-symmetry phases. The states are prepared using a combination of variational and adiabatic evolution methods. First, the ground state of a local Hamiltonian, which includes the φ 4 self-interaction, is prepared using short variational circuits. Next, this state is evolved by switching on the coupling between the lattice sites adiabatically. The parameters defining the local Hamiltonian are adjustable and constitute the input of our algorithm. We present a method to optimize these parameters in order to reduce the adiabatic time required for state preparation. For preparing broken-symmetry states, the adiabatic evolution problems caused by crossing the phase transition critical line and by the degeneracy of the broken-symmetry ground state can be addressed using an auxiliary external field which gradually turns off during the adiabatic process. We show that the time dependence of the external field during the adiabatic evolution is important for addressing the broken-symmetry ground state degeneracy. The adiabatic time dependence on the inverse error tolerance can be reduced from quadratic to linear by using a field strength that decreases exponentially in time relative to one that decreases linearly.
The threat of damage from high speed meteoroid and orbital debris particle impacts has become a significant design consideration in the development and construction of long duration earth-orbiting spacecraft. Historically, significant amounts of resources have been devoted to developing shielding for such structures as a means of reducing the penetration potential of high speed on-orbit impacts. These efforts have typically focused on simply whether or not the inner (or 'pressure') walls of candidate multi-wall structural systems would be perforated. Only recently the nature and extent of pressure wall penetration damage have begun to be explored. This report presents the results of a study whose objective was to characterize the hole formation and cracking phenomena associated with the penetration of the multi-wall systems being considered for the International Space Station Alpha (ISSA).
The daily conduct of high-risk, high-consequence work, by its very nature, can be mentally demanding. Research demonstrates that failure to manage or mitigate these demands can degrade psychological well-being and mental health. Degradations in employee well-being impact individual performance, jeopardizing safety and mission success in the workplace. This Commentary describes efforts taken at Sandia National Laboratories over the past eight years to evaluate, understand, learn from, and mitigate factors such as stress, burnout, work-life imbalances, and disengagement in the workplace that can degrade employee well-being. After evaluating these four facets of employee well-being, Sandia National Laboratories initiated several programs to address observations and outcomes, including the Thrive program, the Take 10 Initiative, work-life balance resources, employee resource groups such as the Sandia Parents Group, and Workplace Improvement Networks. Collectively, the intent of these programs is to ensure employee mental readiness to conduct hazardous high-risk work effectively and safely. Preliminary data suggest that these programs are succeeding. In conclusion, other national laboratories and organizations, regardless of size, may wish to apply similar approaches to improve employee well-being and thereby increase the likelihood of mission success.
In this work, we present a three-stage multiobjective mixed-integer linear programming (MILP) for the optimal expansion planning and operation of isolated multienergy microgrids in remote areas. By selecting the optimal distributed generators (DGs) and energy storage systems (ESSs) mix selection, siting, sizing, and scheduling in the remote microgrid, the proposed model is targeted to minimize the annualized total cost of microgrids while enhancing the performance of the system, i.e., minimizing the voltage deviations and line power loss. To represent the electricity and heat flow between generation resources and various electrical, heating, and cooling loads in the isolated microgrid, linearized power flow, and heat flow constraints are employed in the proposed optimization model. The available capacity of DGs and ESSs are modeled as discrete constants instead of continuous variables for practical purpose. Numerical simulation results on a remote microgrid consisting of DGs, ESSs, and various loads validate the proposed method.
As the basis for virtually any form of nitrogen fertilizers, ammonia plays a vital role in agriculture; in addition, there has been an increased interest in its use as a carbon-free energy carrier. However, ammonia is also associated with two major environmental concerns: CO 2 emissions from the conventional production process and nitrogen pollution from the excessive use of ammonia-based fertilizers. To mitigate these environmental impacts, we develop an optimization framework for the design of a sustainable ammonia-based agricultural system that synergistically integrates the production of ammonia from renewable resources and effective measures for nitrogen management. The proposed model captures the effect of intermittency by incorporating both design and detailed operational decisions. Here, by applying a multiscale time representation that reduces the problem size and a tailored surrogate model that accurately approximates model nonlinearity, we are able to achieve optimal solutions within reasonable computation times. A computational case study is conducted using real-world data from a local farm in Morris, Minnesota, and the results indicate the trade-off between cost and nitrogen loss. Importantly, we show that practicing effective nitrogen management can significantly reduce the nitrogen loss with only a small increase in net present cost.
Machine Learning (ML) has become one of the important tools for High Energy Physics analysis. As the size of the dataset increases at the Large Hadron Collider (LHC), and at the same time the search spaces become bigger and bigger in order to exploit the physics potentials, more and more computing resources are required for processing these ML tasks. In addition, complex advanced ML workflows are developed in which one task may depend on the results of previous tasks. How to make use of vast distributed CPUs/GPUs in WLCG for these big complex ML tasks has become a popular research area. In this paper, we present our efforts enabling the execution of distributed ML workflows on the Production and Distributed Analysis (PanDA) system and intelligent Data Delivery Service (iDDS). First, we describe how PanDA and iDDS deal with large-scale ML workflows, including the implementation to process workloads on diverse and geographically distributed computing resources. Next, we report real-world use cases, such as HyperParameter Optimization, Monte Carlo Toy confidence limits calculation, and Active Learning. Finally, we conclude with future plans.
For several years, the ROOT team is developing the new RNTuple I/O subsystem in preparation of the next generation of collider experiments. Both HL-LHC and DUNE are expected to start data taking by the end of this decade. They pose unprecedented challenges to event data I/O in terms of data rates, event sizes, and event complexity. At the same time, the I/O landscape is becoming more diverse. HPC cluster file systems and object stores, NVMe disk cache layers in analysis facilities, and S3 storage on cloud resources are mixing with traditional XRootD-managed spinning disk pools.The ROOT team will finalize a first production version of the RNTuple binary format by the end of 2024. After this point, ROOT will provide backward compatibility for RNTuple data. This contribution provides an overview of the RNTuple feature set, the related R&D activities and the long-term vision for RNTuple. We report on performance, interface design, tooling, robustness, integration with experiment frameworks, and validation results, as well as recent R&D on parallel reading and writing and exploitation of modern hardware and storage systems. We will give an outlook on possible future features after a first production release.Collaboratively, the IT and EP departments at CERN have launched a formal project within the Research and Computing sector to evaluate the novel data format for physics analysis data utilized in LHC experiments and other fields. This part of the project focuses on validating the scalability of the EOS storage backend during the transition from the over 25 years old TTree production format to the newly developed RNTuple format, using both replicated and erasure-coded storage profiles.
Individual human location trajectory and check-in data have been the driving force for human mobility research in recent years. However, existing human mobility datasets are very limited in size and representativeness. For example, one of the largest and most commonly used datasets of individual human location trajectories, GeoLife, captures fewer than two hundred individuals. To help fill this gap, this Data and Resources paper leverages an existing data generator based on fine-grained simulation of individual human patterns of life to produce large-scale trajectory, check-in, and social network data. In this simulation, individual human agents commute between their home and work locations, visit restaurants to eat, and visit recreational sites to meet friends. We provide large datasets of months of simulated trajectories for two example regions in the United States: San Francisco and New Orleans. In addition to making the datasets available, we also provide instructions on how the simulation can be used to re-generate data, thus allowing researchers to generate the data locally without downloading prohibitively large files.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Tw5 East Pond Wetland. This is the FLUXNET version of the carbon flux data for the site US-Tw5 East Pond Wetland produced by applying the standard ONEFlux (1F) software. Site Description - The Twitchell Wetland site is a 6.5 acre restored wetland on Twitchell Island, that is managed by the California Department of Water Resources (DWR) and the U.S. Geological Survey (USGS). In the fall of 1997, the site was permanently flooded to a depth of approximately 55 cm. The wetland remained fairly unvegetated in patches increasing in size towards the east. The site underwent a major disturbance in 2013 when the vegetation was removed to seed a nearby restored wetland. A flux tower equipped to analyze energy, H2O, CO2, and CH4 fluxes was installed on April 17, 2018.
The author has identified the following significant results. To update and refine existing state-wide land resource information systems, the Minnesota State Planning Agency is assessing the feasibility of extracting resource information from ERTS-1 imagery. Work has centered on a comparative analysis of Minnesota Land Management Information System (MLMIS) and ERTS-1 land use classes. The associated problems of determining appropriate data cell size and optimal seasonal timing have also been addressed. Using ERTS-1 images, dominant land use is classified as follows: urban, forest, agriculture, extractive, transportation, water, and wetlands. Preliminary analysis suggests that with appropriate changes in operational definitions these general classes can be further refined for the benefit of MLMIS users. Additional detail appears most feasible extractive classes.
There are several preliminary, or pilot, efforts for developing data systems for supporting NASA science research. The Pilot Data Systems consist of the Pilot Land Data System (PLDS), the Pilot Ocean Data System (PODS), the Pilot Climate Data System (PCDS), and the Pilot Planetary Data System (PPDS). The PLDS is likely to have the greatest communication needs of the various pilots. Communications issues and requirements are examined in the context of the mature PLDS as it may exist by 1990. The PLDS is seen as a distributed processing system linking resources at a number of NASA research centers and outside universities. Large image data sets, including LANDSAT scenes, are a major data type to be moved along the PLDS communications network. The unusually large size of these data files requires examining new technologies that may allow efficient and affordable communication at rates of up to 60 megabits per second. Potentially useful developments include portable satellite ground stations, and time division multiple access for sharing high-speed satellite links. Further pooling of communications for the various data systems into a single network would reduce costs and may make economic justification of access to the required data rates possible.
The far-IR band is uniquely suited to study the physical conditions in the interstellar medium from nearby sources out to the highest redshifts. FIR imaging and spectroscopy instrumentation using incoherent superconducting bolometers represents a high sensitivity technology for many future suborbital and space missions, including the Origins Space Telescope. Robust, high sensitivity detector arrays with several 104 pixels, large focal plane filling factors, and low cosmic ray cross sections that operate over the entire far-IR regime are required for such missions. These arrays could consist of smaller sub-arrays, in case they are tileable. The TES based Backshort Under Grid array architecture which our group has fielded in a number of FIR cameras, is a good candidate to meet these requirements: BUGs are tileable, and with the integration of the SQUID multiplexer scaleable beyond wafer sizes; they provide high filling factors, low cosmic cross section and have been demonstrated successfully in far-infrared astronomical instrumentation. However, the production of BUGs with integrated readout multiplexers has many time and resource consuming process steps. In order to meet the requirement of robustness and efficiency on the production of future arrays, we have developed a new method to provide the superconducting connection of BUG detectors to the readout multiplexers or general readout boards behind the detectors. This approach should allow us to reach the goal to produce reliable, very large detector arrays for future FIR missions.
High Performance Computing (HPC) has become an integral part of NASAs Aeronautics research and application endeavors. HPC requirements for Aeroscience applications are increasing by leaps and bounds as scientists and engineers increase the fidelity of the simulations and the size of the engineering databases needed for NASA missions. In this talk we present several such applications and describe how they have benefited from the use of supercomputing. We provide an overview of the resources available at NASA Advanced Supercomputing (NAS) facility at Ames Research Center in Silicon Valley, and also describe the progress in performance of Computational Fluid Dynamics (CFD) codes on current and future HPC technologies. We also discuss some of the challenges in efficiently exploiting the underlying computational resources for such codes.
Since the first full-scale weather satellite Television Infrared Observation Satellite (TIROS)-1 was launched in 1960 to measure weather patterns from space, the number of satellites carrying various sensors to measure atmospheric properties has increased rapidly. Data from these meteorological satellites have been crucial to the advancement of the NWP forecasts. Especially, space-borne measurements of atmospheric temperature and moisture information provided by microwave sounders were reported to contribute most to positive impacts on global NWP forecasts. Developing and launching an operational weather satellite is a daunting and tremendously expensive mission that requires many years of planning, developments, and maintenance after the launch. Small satellites with low size, weight, and power requirements can reduce the cost associated with the construction and launch of large bus platforms and draw attention of several space agencies and weather technology companies that started investing their resources to develop small satellites and measure the potential benefits and weaknesses. The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of small satellites carrying state-of-art microwave temperature and humidity sounders with 12 channels between 91 GHz and 205 GHz frequency. Currently five TROPICS cubsats, including TROPICS-pathfinder, are in space and provide the temperature and humidity data from space to the meteorological community. This study seeks to assess the potential impact that the constellation of TROPICS satellites may bring to the global NWP analysis and forecasts by assimilating all-sky TROPICS data and implementing observing system experiments (OSE) using the NASA GEOS system. Various evaluations metrics including forecast skills, fit to other observations such as radiosondes and microwave and infrared sounder are used. Along with the NWP impact assessment, the quality of the TROPICS data is evaluated by looking at observation minus forecast statistics in comparisons with other conventional satellite temperature and humidity sounders.
Since the first full-scale weather satellite Television Infrared Observation Satellite (TIROS)-1 was launched in 1960 to measure weather patterns from space, the number of satellites carrying various sensors to measure atmospheric properties has increased rapidly. Data from these meteorological satellites have been crucial to the advancement of the NWP forecasts. Especially, space-borne measurements of atmospheric temperature and moisture information provided by microwave sounders were reported to contribute most to positive impacts on global NWP forecasts. Developing and launching an operational weather satellite is a daunting and tremendously expensive mission that requires many years of planning, developments, and maintenance after the launch. Small satellites with low size, weight, and power requirements can reduce the cost associated with the construction and launch of large bus platforms and draw attention of several space agencies and weather technology companies that started investing their resources to develop small satellites and measure the potential benefits and weaknesses. The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of small satellites carrying state-of-art microwave temperature and humidity sounders with 12 channels between 91 GHz and 205 GHz frequency. Currently five TROPICS cubsats, including TROPICS-pathfinder, are in space and provide the temperature and humidity data from space to the meteorological community. This study seeks to assess the potential impact that the constellation of TROPICS satellites may bring to the global NWP analysis and forecasts by assimilating all-sky TROPICS data and implementing observing system experiments (OSE) using the NASA GEOS system. Various evaluations metrics including forecast skills, fit to other observations such as radiosondes and microwave and infrared sounder are used. Along with the NWP impact assessment, the quality of the TROPICS data is evaluated by looking at observation minus forecast statistics in comparisons with other conventional satellite temperature and humidity sounders.