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At least 595 records · Page 33

Microwave Radiometers from 0.6 to 22 GHz for Juno, A Polar Orbiter Around Jupiter

A compact instrument called the MWR (MicroWave Radiometer) is under development at JPL for Juno, the next NASA New Frontiers mission, scheduled to launch in 2011. It's purpose is to measure the thermal emission from Jupiter's atmosphere at six selected frequencies from 0.6 to 22 GHz, operating in direct detection mode, in order to quantify the distributions and abundances of water and ammonia in Jupiter's atmosphere. The goal is to understand the previously unobserved dynamics of the sub-cloud atmosphere, and to discriminate among models for planetary formation in our solar system. As part of a deep space mission aboard a solar-powered spacecraft, MWR is designed to be compact, lightweight, and low power. The receivers and control electronics are protected by a radiation-shielding enclosure on the Juno spacecraft that would provide a benign and stable operating temperature environment. All antennas and RF transmission lines outside the vault must withstand low temperatures and the harsh radiation environment surrounding Jupiter. This paper describes the concept of the MWR instrument and presents results of one breadboard receiver channel.

Antenna↗

Planning to Explore: Using a Coordinated Multisource Infrastructure to Overcome Present and Future Space Flight Planning Challenges

Few human endeavors present as much of a planning and scheduling challenge as space flight, particularly manned space flight. Just on the operational side of it, efforts of thousands of people across hundreds of organizations need to be coordinated. Numerous tasks of varying complexity and nature, from scientific to construction, need to be accomplished within limited mission time frames. Resources need to be carefully managed and contingencies worked out, often on a very short notice. From the beginning of the NASA space program, planning has been done by large teams of domain experts working months, sometimes years, to put together a single mission. This approach, while proven very reliable up to now, is becoming increasingly harder to sustain. Elevated levels of NASA space activities, from deployment of the new Crew Exploration Vehicle (CEV) and completion of the International Space Station (ISS), to the planned lunar missions and permanent lunar bases, will put an even greater strain on this largely manual process. While several attempts to automate it have been made in the past, none have fully succeeded. In this paper we describe the current NASA planning methods, outline their advantages and disadvantages, discuss the planning challenges of upcoming missions and propose a distributed planning/scheduling framework (CMMD) aimed at unifying and optimizing the planning effort. CMMD will not attempt to make the process completely automated, but rather serve in a decision support capacity for human managers and planners. It will help manage information gathering, creation of partial and consolidated schedules, inter-team negotiations, contingencies investigation, and rapid re-planning when the situation demands it. The fist area of CMMD application will be planning for Extravehicular Activities (EVA) and associated logistics. Other potential applications, not only in the space flight domain, and future research efforts will be discussed as well.

Balaban, Edward↗

Illinois Express Quantum Network (IEQNET): metropolitan-scale experimental quantum networking over deployed optical fiber

The Illinois Express Quantum Network (IEQNET) is a program to realize metro-scale quantum networking over deployed optical fiber using currently available technology. IEQNET consists of multiple sites that are geographically dispersed in the Chicago metropolitan area. Each site has one or more quantum nodes (Qnodes) representing the communication parties in a quantum network. Q-nodes generate or measure quantum signals such as entangled photons and communicate the results via standard, classical, means. The entangled photons in IEQNET nodes are generated at multiple wavelengths, and are selectively distributed to the desired users via optical switches. Here we describe the network architecture of IEQNET, including the Internet-inspired layered hierarchy that leverages software-defined-networking (SDN) technology to perform traditional wavelength routing and assignment between the Q-nodes. Specifically, SDN decouples the control and data planes, with the control plane being entirely classical. Issues associated with synchronization, calibration, network monitoring, and scheduling will be discussed. An important goal of IEQNET is demonstrating the extent to which the control plane can coexist with the data plane using the same fiber lines. This goal is furthered by the use of tunable narrow-band optical filtering at the receivers and, at least in some cases, a wide wavelength separation between the quantum and classical channels. We envision IEQNET to aid in developing robust and practical quantum networks by demonstrating metro-scale quantum communication tasks such as entanglement distribution and quantum-state teleportation.

Chung, Joaquin↗

Controlled workplace charging of electric vehicles: The impact of rate schedules on transformer aging

To accelerate adoption of non-residential charging for electric vehicles, sites must maximize utilization of existing electrical infrastructure. In this study we model electric vehicle charging at a workplace using real charging data and evaluate the lifetime of the site’s transformer as the number of charging stations is incrementally increased. We implement and compare a range of control schemes for workplace charging including minimizing the peak load, capping the total load, minimizing bills under different rate structures with time-of-use energy costs and demand charges, and directly minimizing the transformer’s aging. These are compared by the number of vehicles they allow the transformer to support, the transformer’s health, and the operator’s electricity bill. We draw a connection between minimizing the peak load and improving the transformer’s health. We observe that minimizing the electricity bill is the best scheme by both criteria when the bill includes a demand charge; in our experiment it allowed the infrastructure to support over 67% more cars than under uncontrolled charging. To protect the transformer we recommend that demand charges or capacity management be applied to parking lots of charging electric vehicles with high infrastructure utilization, and operators schedule charging to minimize their electricity bills.

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A Planning Revolution

The traditional centralized planning and scheduling of complex fast moving projects are value-added activites. However, centralized scheduling has some severe deficiencies that have plagued managers since the Polaris project when PERT analysis was invented.

planning project control receivables delivarables ↗

Hydropower Role in a Power Grid with a High Proportion of Variable Renewables

The importance of hydropower increases as the power grid evolves with the higher variable renewable contribution. As conventional thermal power plants are retired, the importance of hydropower contribution increases to balance the variability of solar and wind generation. However, reservoir water resources are constrained by multiple constraints, and variability of water inflow to the reservoirs creates limitations to dam water releases for power grid needs. Coordination of multiple tools, including water resources modeling, ecological modeling, and technical and economic power grid modeling, informs dam water releases. Better representation of ecological constraints and other water use details in the suit of power grid models are required to identify the hydropower flexibility to provide multiple power grid services. Impacts of water planning and hydropower operation changes to a power grid are better understood by production cost model simulations with technical and economic data, including unserved energy, reserve failures, transmission congestion to serve load, and local marginal price increases. Similarly, PCM simulation of current and future projected power grid information, including LMP, and carbon emission rates, informs short-term water release plans and long-term investments for power plant upgrades for technical and ecological needs. Hydropower operations of several case studies are simulated to understand operation patterns, revenue, water release decisions in multiple time scales (month, day, minutes), hydropower contracts scheduling, and water variability impacts.

environmental↗

Smarter building start – A distributed solution

A significant focus of research and new technologies for reducing energy use in buildings is on operating the systems more efficiently during the times when the systems are active. However, there is a large potential for energy savings in determining the periods when the systems should or should not be active. This scheduling aspect of operation is often overlooked even though relatively simple solutions can unlock substantial energy savings. In this paper we describe a smart building start (SBS) algorithm that considers multiple zones in a building to determine individual schedules for room controllers as well as the central systems based on solving a simple optimization problem. Application of the SBS algorithm to multiple interconnected systems enables a staggered start-up that minimizes peak loads and also ensures comfort is within a target range with minimal system run time. The SBS algorithm extends the capability of traditional optimal start and is designed to be simple to deploy and robust. Simulation results as well as results from tests in a real building with a VAV system are presented. The presented algorithm is applicable to any type of building with a zonal or multi-zone HVAC system. To function, it needs to be able to change setpoints in rooms and monitor room temperatures, as well as, if desired, turn the central system on or off.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Tri-level hybrid interval-stochastic optimal scheduling for flexible residential loads under GAN-assisted multiple uncertainties

Various building loads, such as heating, ventilation, and air conditioners (HVACs), electric water heaters (EWHs), and electric vehicles (EVs), can introduce opportunities for improving the flexibility of electricity consumption while satisfying the needs of building owners as well as benefiting the resilience of distribution system. To utilize such flexibility, a tri-level distribution market framework is established, including residential consumers, load aggregators (LAs), and the distribution system operator (DSO). In this work, the uncertainties from all three levels are considered. The random consumption behavior at the consumer level is modeled as a Gaussian noise that is also aggregated and transmitted to the LA level. The weather temperature in the LA level is forecasted as an interval, and the photovoltaic (PV) power in the market-clearing level is modeled by a set of power scenarios generated by Generative Adversarial Networks (GANs). Then, a hybrid interval-stochastic programming is proposed to transform the uncertain problems in the first two levels into deterministic ones. For real-time implementations, a rolling horizon optimization (RHO) scheme is employed to continuously optimize the power consumption based on the latest operating information. Finally, case studies on a modified IEEE 69-bus system validate the effectiveness of the proposed uncertainty modeling strategies and the RHO scheme.

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Prototype energy models for data centers

Data centers in the United States consume about two percent of the nation’s electricity. Because heat gains from IT equipment drive cooling demand, data centers offer unique opportunities for energy savings. However, no prototype energy model for data centers is available in the suite of existing U.S. Department of Energy’s Commercial Prototype Building Models. Here we present the development of two new data center prototype models and their implementation in OpenStudio and EnergyPlus. The small-size data center model represents a computer room in a building served by computer room air conditioners (CRACs); while the large-sized model represents stand-alone data centers served by computer room air handlers (CRAHs) with a central chiller plant. For each data center model, two levels of IT equipment (ITE) load density were considered, to cover the wide range of IT power density of data centers: 40 and 100 W/ft 2 (430 and 1076 W/m 2 ) for the computer room, and 100 and 500 W/ft 2 (1076 and 5382 W/m 2 ) for the stand-alone data center. All other assumptions, such as building envelope, lighting, HVAC efficiencies and schedules, were based on the minimal requirements of ASHRAE Standard 90.1 at various vintages. We introduced a novel concept of supply and return air approach temperatures to capture the essential effects of non-uniform airflow and temperature distribution in data centers. The approach temperatures were pre-computed by computational fluid dynamics (CFD) simulations for various configurations of ITE loads and airflow containment management in data centers. A new feature was developed in EnergyPlus to implement the approach temperature method. A case study was conducted to demonstrate the use of the data center models. The two data center models cover all U.S. climate zones and can be used to evaluate energy saving measures for data centers, as well as to support development of data center energy efficiency codes and standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Probabilistic Zonal Reserve Requirements for Improved Energy Deliverability with Wind Power

In power systems with high penetration of renewable energy resources, uncertainty and variability of these stochastic resources introduce additional challenges for the operation of power systems. To improve the power system's reliability in the face of uncertainty, reserves are required as additional generation capacity to rebalance the power system following random disturbances. However, reserve deliverability is not guaranteed, because it may encounter potential transmission line congestion. Zonal reserve requirements can address this issue, but operators lack efficient ways to allocate reserves to zones while accounting for wind power forecast uncertainty. Herein we propose a methodology for probabilistic zonal reserve requirements to address wind power forecast uncertainties. This method estimates the probability distribution of line flows based on the system generation margin and injection shift factor. This estimate is then used to construct pre-defined and post-zonal reserve requirements. Case studies demonstrate that the proposed method efficiently schedules energy and reserves to balance energy and manage deliverability with wind power forecast uncertainty.We also discuss operational implications of the proposed method.

17 WIND ENERGY↗

Version 0 EOSDIS - An overview

Attention is given to NASA's Earth Observing System Data and Information System (EOSDIS), which is to be a single, distributed but internally consistent evolutionary system to support the planning and execution of EOS data acquisitions and to process, archive, and distribute EOS data products and selected non-EOS data to enable interdisciplinary studies of the earth. V0 EOSDIS, a logical step in this evolutionary process, is to address both technical and managerial challenges. Technical challenges include developing a multidiscipline, distributed system for searching and ordering data in a heterogeneous environment, and standardizing data formats and distribution techniques among differing communities and organizations. Managerial challenges include establishing and maintaining a structure consisting of geographically distributed entities such that cooperative development is carried out effectively despite organizational differences, maintaining interactions with the scientific community to ensure its close involvement despite its size and diversity, and keeping the expectations for V0 consistent with its schedules and resources.

Ramapriyan, H. K.↗

Potential Refinement of the ICRF

The analysis and data used for the ICRF represented the state of the art in global, extragalactic, X/S band microwave astrometry in 1995. The same general analysis method was used to extend the ICRF with subsequent VLBI data in a manner consistent with the original catalog. Since 1995 there have been considerable advances in the geodetic/astrometric VLBI data set and in the analysis that would significantly improve the systematic errors, stability, and density of the next realization of the ICRS when the decision is made to take this step. In particular, data acquired since 1990, including extensive use of the VLBA, are of higher quality and astrometric utility because of changes in instrumentation, schedule design, and networks as well as specifically astrometric intent. The IVS (International VLBI Service for Geodesy and Astrometry) continues to devote a portion of its observing capability to systematic extension of the astrometric data set. Sufficient data distribution exists to select a better set of defining sources. Improvements in troposphere modeling will minimize known systematic astrometric errors while accurate modeling and estimation of station effects from loading and nonlinear motions will permit the reintegration of the celestial reference frame, terrestrial reference frame and Earth orientation parameters though a single VLBI solution. The differences between the current ICRF and the potential next realization will be described.

Ma, Chopo↗

NASA Spacecraft Fault Management Workshop Results

Fault Management is a critical aspect of deep-space missions. For the purposes of this paper, fault management is defined as the ability of a system to detect, isolate, and mitigate events that impact, or have the potential to impact, nominal mission operations. The fault management capabilities are commonly distributed across flight and ground subsystems, impacting hardware, software, and mission operations designs. The National Aeronautics and Space Administration (NASA) Discovery & New Frontiers (D&NF) Program Office at Marshall Space Flight Center (MSFC) recently studied cost overruns and schedule delays for 5 missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that 4 out of the 5 missions studied had significant overruns due to underestimating the complexity and support requirements for fault management. As a result of this and other recent experiences, the NASA Science Mission Directorate (SMD) Planetary Science Division (PSD) commissioned a workshop to bring together invited participants across government, industry, academia to assess the state of the art in fault management practice and research, identify current and potential issues, and make recommendations for addressing these issues. The workshop was held in New Orleans in April of 2008. The workshop concluded that fault management is not being limited by technology, but rather by a lack of emphasis and discipline in both the engineering and programmatic dimensions. Some of the areas cited in the findings include different, conflicting, and changing institutional goals and risk postures; unclear ownership of end-to-end fault management engineering; inadequate understanding of the impact of mission-level requirements on fault management complexity; and practices, processes, and tools that have not kept pace with the increasing complexity of mission requirements and spacecraft systems. This paper summarizes the findings and recommendations from that workshop, as well as opportunities identified for future investment in tools, processes, and products to facilitate the development of space flight fault management capabilities.

Newhouse, Marilyn↗

Results from the NASA Spacecraft Fault Management Workshop: Cost Drivers for Deep Space Missions

Fault Management, the detection of and response to in-flight anomalies, is a critical aspect of deep-space missions. Fault management capabilities are commonly distributed across flight and ground subsystems, impacting hardware, software, and mission operations designs. The National Aeronautics and Space Administration (NASA) Discovery & New Frontiers (D&NF) Program Office at Marshall Space Flight Center (MSFC) recently studied cost overruns and schedule delays for five missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that four out of the five missions studied had significant overruns due to underestimating the complexity and support requirements for fault management. As a result of this and other recent experiences, the NASA Science Mission Directorate (SMD) Planetary Science Division (PSD) commissioned a workshop to bring together invited participants across government, industry, and academia to assess the state of the art in fault management practice and research, identify current and potential issues, and make recommendations for addressing these issues. The workshop was held in New Orleans in April of 2008. The workshop concluded that fault management is not being limited by technology, but rather by a lack of emphasis and discipline in both the engineering and programmatic dimensions. Some of the areas cited in the findings include different, conflicting, and changing institutional goals and risk postures; unclear ownership of end-to-end fault management engineering; inadequate understanding of the impact of mission-level requirements on fault management complexity; and practices, processes, and tools that have not kept pace with the increasing complexity of mission requirements and spacecraft systems. This paper summarizes the findings and recommendations from that workshop, particularly as fault management development issues affect operations and the development of operations capabilities.

Newhouse, Marilyn E.↗

Masked Proportional Routing

Masked proportional routing is an improved procedure for choosing links between adjacent nodes of a network for the purpose of transporting an entity from a source node ("A") to a destination node ("B"). The entity could be, for example, a physical object to be shipped, in which case the nodes would represent waypoints and the links would represent roads or other paths between waypoints. For another example, the entity could be a message or packet of data to be transmitted from A to B, in which case the nodes could be computer-controlled switching stations and the links could be communication channels between the stations. In yet another example, an entity could represent a workpiece while links and nodes could represent, respectively, manufacturing processes and stages in the progress of the workpiece towards a finished product. More generally, the nodes could represent states of an entity and the links could represent allowed transitions of the entity. The purpose of masked proportional routing and of related prior routing procedures is to schedule transitions of entities from their initial states ("A") to their final states ("B") in such a manner as to minimize a cost or to attain some other measure of optimality or efficiency. Masked proportional routing follows a distributed (in the sense of decentralized) approach to probabilistically or deterministically choosing the links. It was developed to satisfy a need for a routing procedure that 1. Does not always choose the same link(s), even for two instances characterized by identical estimated values of associated cost functions; 2. Enables a graceful transition from one set of links to another set of links as the circumstances of operation of the network change over time; 3. Is preferably amenable to separate optimization of different portions of the network; 4. Is preferably usable in a network in which some of the routing decisions are made by one or more other procedure(s); 5. Preferably does not cause an entity to visit the same node twice; and 6. Preferably can be modified so that separate entities moving from A to B do not arrive out of order.

Wolpert, David↗

Benefit Assessment of the Precision Departure Release Capability Concept

A Precision Departure Release Capability concept is being evaluated by both the National Aeronautics and Space Administration and the Federal Aviation Administration as part of a larger goal of improving throughput, efficiency and capacity in integrated departure, arrival and surface operations. The concept is believed to have the potential of increasing flight efficiency and throughput by avoiding missing assigned slots and minimizing speed increase or path stretch to recover the slot. The main thrust of the paper is determining the impact of early and late departures from the departure runway when an aircraft has a slot assigned either at a meter fix or at the arrival airport. Results reported in the paper are for two scenarios. The first scenario considers flights out of Dallas/Fort Worth destined for Hartsfield-Jackson International Airport in Atlanta flying through the Meridian meter-fix in the Memphis Center with miles-in-trail constraints. The second scenario considers flights destined to George Bush Intercontinental/Houston Airport with specified airport arrival rate constraint. Results show that delay reduction can be achieved by allowing reasonable speed changes in scheduling. It was determined that the traffic volume between Dallas/Fort Worth and Atlanta via the Meridian fix is low and the departures times are spread enough that large departure schedule uncertainty can be tolerated. Flights can depart early or late within 90 minutes without accruing much more delay due to miles-in-trail constraint at the Meridian fix. In the Houston scenario, 808 arrivals from 174 airports were considered. Results show that delay experienced by the 16 Dallas/Fort Worth departures is higher if initial schedules of the remaining 792 flights are kept unaltered while they are rescheduled. Analysis shows that the probability of getting the initially assigned slot back after perturbation and rescheduling decreases with increasing standard deviation of the departure delay distributions. Results show that most Houston arrivals can be expected to be on time based on the assumed zero-mean Normal departure delay distributions achievable by Precision Departure Release Capability. In the current system, airport-departure delay, which is the sum of gate-departure delay and taxi-out delay, is observed at the airports. This delay acts as a bias, which can be reduced by Precision Departure Release Capability.

Palopo, Kee↗

Preparing for Delivery of the Lunar Ice Cube Compact IR Spectrometer Payload

Lunar Ice Cube, scheduled to be launched on ARTEMIS I in late 2021, is a deep space cubesat mission with the goalsof demonstrating 1) a cubesat-scale instrument (BIRCHES) capable of addressing NASA HEOMD Strategic KnowledgeGaps related to lunar volatile distribution (abundance, location, and transportation physics of water ice), and 2) cubesatpropulsion, via the Busek BIT 3 RF Ion engine. The mission will also demonstrate the AIM/IRIS microcryocooler for thefirst time in deep space. BIRCHES integration is nearly complete, with several changes made to the thermal design toimprove detector performance. Final preflight instrument testing and calibration, our ongoing concern to be emphasizedhere, have been delayed due to the mandated closure rules of NASA facilities. Lunar Ice Cube, along with two othercubesats deployed from ARTEMIS I, Lunar Flashlight and LunaH-Map, will be the first deep cubesat missions to deliverscience data to the Planetary Data System.

Mason, D.↗

Intelligent Partitioning based Fully Parallel AC Security-Constrained Optimal Power Flow

Today’s power grid is becoming more diverse and integrated with high-level distributed energy resources and smart control technologies that is creating a new set of grid management challenges in terms of large-scale, nonlinear, and non-convex problem modeling, complex and time-consuming computation, as well as difficult uncertainty handling. This project focused on solving a challenging multi-period security-constrained generation scheduling problem, which is of great importance for maximizing the social welfare of real-time dispatch, day-ahead market, as well as weekly planning of power systems. Our developed software explored parallel optimization algorithms for complex and realistic power system models, and develop fast, efficient, and robust grid optimization solutions on the high-performance computing platform that will enable increased grid economics, flexibility, resilience, as well as energy security in the United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗