SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Project cost risk is the uncertainty in final project cost, contingent on initial budget, requirements and schedule. For a proposed mission, a dynamic simulation model relying for some of its input on a simple risk elicitation is used to identify and quantify systemic cost risk.
This paper presents the capabilities implemented in the SAX system for an efficient operations management during its in-flight mission. SAX is an Italian scientific satellite for x-ray astronomy whose major mission objectives impose quite tight constraints on the implementation of both the space and ground segment. The most relevant mission characteristics require an operative lifetime of two years, performing scientific observations both in contact and in noncontact periods, with a low equatorial orbit supported by one ground station, so that only a few minutes of communications are available each orbit. This operational scenario determines the need to have a satellite capable of performing the scheduled mission automatically and reacting autonomously to contingency situations. The implementation approach of the on-board operations management, through which the necessary automation and autonomy are achieved, follows a hierarchical structure. This has been achieved adopting a distributed avionic architecture. Nine different on-board computers, in fact, constitute the on-board data management system. Each of them performs the local control and monitors its own functions while the system level control is performed at a higher level by the data handling applications software. The SAX on-board architecture provides the ground operators with different options of intervention by three classes of telecommands. The management of the scientific operations will be scheduled by the operation control center via dedicated operating plans. The SAX satellite flight mode is presently being integrated at Alenia Spazio premises in Turin for a launch scheduled for the end of 1995. Once in orbit, the SAX satellite will be subject to intensive check-out activities in order to verify the required mission performances. An overview of the envisaged procedure and of the necessary on-ground activities is therefore depicted as well.
In-flight maintenance, as conceived and preplanned for the Skylab mission was limited to simple scheduled and unscheduled replacement tasks and minor contingency repairs. Tools and spares were provided accordingly. However, failures during the mission dictated complicated and sophisticated repairs to major systems so that the mission could continue. These repairs included the release of a large structure that failed to deploy, the assembly and deployment of large mechanical devices, the installation and checkout of precision electronic equipment, troubleshooting and repair of precision electromechanical equipment, and tapping into and recharging a cooling system. The repairs were conducted both inside the spacecraft and during extravehicular activities. Some of the repair tasks required team effort on the part of the crewmen including close procedural coordination between internal and extravehicular crewmen. The Skylab experience indicates that crewmen can, with adequate training, make major system repairs in space using standard or special tools. Design of future spacecraft systems should acknowledge this capability and provide for more extensive in-flight repair and maintenance.
In-flight maintenance, as conceived and pre-planned for the Skylab Mission, was limited to simple scheduled and unscheduled replacement tasks and minor contingency repairs. Failures during the mission dictated complicated and sophisticated repairs to major systems so that the mission could continue. These repairs include the release of a large structure that failed to deploy, the assembly and deployment of large mechanical devices, the installation and checkout of precision electronic equipment, troubleshooting and repair of precision electromechanical equipment and tapping into and recharging a cooling system. The Skylab experience proves conclusively that crewmen can, with adequate training, make major system repairs in space using standard or special tools.
George Diller of NASA Public Affairs hosted this briefing. Pete Nickolenko, NASA Test Director; Scott Higgenbotham, STS-114 Payload-Mission Manager; Cathy Winters, Shuttle Weather Officer were present. Pete reports his team has completed the avionics system check ups, servicing of the cryogenic tanks will take about seven hours that day, and will perform engine system checks and pad close outs come evening. Pete also summarized other standard close out activities: check ups of the Orbiter and ground communications network, rotary service, structure retraction, and external tank load (ETL). Pete reported that the mission will be 12 days with two weather contingency days, and end of mission landing scheduled at Kennedy Space Center (KSC) at approximately 11:00 in the morning, Eastern time on July 25th. Scott briefly reported that all hardware is on board Discovery, closed out, and ready to fly. Cathy reported that hurricane Dennis moved to the North and looking forward to launch. She mentioned of a new hurricane looming and will be named Emily, spotted some crosswinds which will migrate to the west, there is 30% probability weather prohibiting launch. Cathy further gave current weather forecast supported with charts: the Launch Forecast, Tanking Forecast, SRB (Shuttle Solid Rocket Booster) Forecast, CONUS and TAL Launch Sites Forecast, and with 24 hours and 48 hours turn around plan. Launch constraints, weather, crosswinds, cloud cover, ground imagery system, launch countdown, launch crews, mission management simulations, launch team simulations were topics covered with the News Media.
Major results of a study applying automation and robotics to lunar surface base buildup and operations concepts are reported. The study developed a reference base scenario with specific goals, equipment concepts, robot concepts, activity schedules and buildup manifests. It examined crew roles, contingency cases and system reliability, and proposed a set of technologies appropriate and necessary for effective lunar operations. This paper refers readers to four companion papers for quantitative details where appropriate.
Prior to beginning a 90-day test of a regenerative life support system, a need was identified for a training and certification program to qualify an operating staff for conducting the test. The staff was responsible for operating and maintaining the test facility, monitoring and ensuring crew safety, and implementing procedures to ensure effective mission performance with good data collection and analysis. The training program was designed to ensure that each operating staff member was capable of performing his assigned function and was sufficiently cross-trained to serve at certain other positions on a contingency basis. Complicating the training program were budget and schedule limitations, and the high level of sophistication of test systems.
Knowledge of irrigation is essential to support food security, manage depleting water resources, and comprehensively understand the global water and energy cycles. Despite the importance of understanding irrigation, little consistent information exists on the amount of water that is applied for irrigation. In this study, we develop and evaluate a new method to predict daily to seasonal irrigation magnitude using a particle batch smoother data assimilation approach, where land surface model soil moisture is applied in different configurations to understand how characteristics of remotely sensed soil moisture may impact the performance of the method. The study employs a suite of synthetic data assimilation experiments, allowing for systematic diagnosis of known error sources. Assimilation of daily synthetic soil moisture observations with zero noise produces irrigation estimates with a seasonal bias of 0.66% and a correlation of 0.95 relative to a known truth irrigation. When synthetic observations were subjected to an irregular overpass interval and random noise similar to the Soil Moisture Active Passive satellite (0.04 cm(exp 3) cm(exp -3)), irrigation estimates produced a median seasonal bias of <1% and a correlation of 0.69. When systematic biases commensurate with those between NLDAS‐2 land surface models and Soil Moisture Active Passive are imposed, irrigation estimates show larger biases. In this application, the particle batch smoother outperformed the particle filter. The presented framework has the potential to provide new information into irrigation magnitude over spatially continuous domains, yet its broad applicability is contingent upon identifying new method(s) of determining irrigation schedule and correcting biases between observed and simulated soil moisture, as these errors markedly degraded performance.
Description of the development and operation of a vehicle-scheduling algorithm which has applications to the NASA problem of assigning payloads to space delivery vehicles. The algorithm is based on a discrete, integer-valued, nonserial, dynamic-programming solution to the classical problem of developing resource utilization plans with limited resources. The algorithm places special emphasis on incorporating interpayload (precedence) relationships; maintaining optimal alternate schedule definitions (a unique feature of dynamic programming) in the event of contingencies (namely, resource inventory changes) without problem resolution; and, by using a special information storage technique, reducing the computational complexity of solving realistic problems.
Schedules for the fifth Space Shuttle flight are provided. Launching procedure, extravehicular activity, contingency plans, satellite deployment, and onboard experiments are discussed. Landing procedures, tracking facilities, and crew data are provided.
As crewed spacecraft have grown larger and more complex, they have come to rely on spacewalks, or Extravehicular Activities (EVA), for assembly and to assure mission success. Typically, these spacecraft maintain all of the hardware and trained personnel needed to perform an EVA on-board at all times. Maintaining this capability requires up-mass, volume for storage of EVA hardware, crew time for ground and on-orbit training, and on-orbit maintenance of EVA hardware. This paper proposes an alternative methodology, utilizing either launch-on-need hardware and crew or regularly scheduled missions to provide EVA capability for space stations in low Earth orbit after assembly complete. Much the same way that one would call a repairman to fix something at their home these EVAs are dedicated to maintenance and upgrades of the orbiting station. For crew safety contingencies it is assumed the station would be designed such the crew could either solve those issues from inside the spacecraft or use the docked Earth to Orbit vehicles as a return lifeboat, in the same manner as the International Space Station (ISS) which does not rely on EVA for crew safety related contingencies. This approach would reduce ground training requirements for long duration crews, save Intravehicular Activity (IVA) crew time in the form of EVA hardware maintenance and on-orbit training, and lead to more efficient EVAs because they would be performed by specialists with detailed knowledge and training stemming from their direct involvement in the development of the EVA. The on-orbit crew would then be available to focus on the immediate response to any failures such as IVA systems reconfiguration or jumper installation as well as the day-to-day operations of the spacecraft and payloads. This paper will look at how current unplanned EVAs are conducted on ISS, including the time required for preparation, and offer an alternative for future spacecraft. As this methodology relies on the on-time and on-need launch of spacecraft, any space station that utilized this approach would need a robust transportation system, possibly including more than one launch vehicle capable of carrying crew. In addition, the fault tolerance of the future space station would be an important consideration in how much time was available for EVA preparation after the failure. Ideally the fault tolerance of the station would allow for the maintenance tasks to be grouped such that they could be handled by regularly scheduled maintenance visits and not contingency launches. Each future program would have to weigh the risk of on-time launch against the increase in available crew time for the main objective of the spacecraft. This is only one of several ideas that could be used to reduce or eliminate a station's reliance on rapid turnaround EVAs using on-board crew. Others could include having shirt-sleeve access to critical systems or utilizing low pressure temporarily pressurized equipment bays.
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.
The estimated plant capital cost for a coal fired 200 MWE electric generating plant with open cycle magnetohydrodynamics is divided into principal accounts based on Federal Energy Regulatory Commision account structure. Each principal account is defined and its estimated cost subdivided into identifiable and major equipment systems. The cost data sources for compiling the estimates, cost parameters, allotments, assumptions, and contingencies, are discussed. Uncertainties associated with developing the costs are quantified to show the confidence level acquired. Guidelines established in preparing the estimated costs are included. Based on an overall milestone schedule related to conventional power plant scheduling experience and starting procurement of MHD components during the preliminary design phase there is a 6 1/2-year construction period. The duration of the project from start to commercial operation is 79 months. The engineering phase of the project is 4 1/2 years; the construction duration following the start of the man power block is 37 months.
The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10 minutes. The models have been extensively tested using a case study for the Space Station Freedom and the results for the case study will be presented. Several future enhancements of the pre-scheduler and the 'rescheduler' have been outlined which include graphic analyzer for the on-line module, incorporating probabilistic considerations, including spatial location of the loads and the connectivity using a direct current (DC) load flow model.
In November 2004, NASA's Space Shuttle Program approved the development of the Extravehicular (EVA) Infrared (IR) Camera to test the application of infrared thermography to on-orbit reinforced carbon-carbon (RCC) damage detection. A multi-center team composed of members from NASA's Johnson Space Center (JSC), Langley Research Center (LaRC), and Goddard Space Flight Center (GSFC) was formed to develop the camera system and plan a flight test. The initial development schedule called for the delivery of the system in time to support STS-115 in late 2005. At the request of Shuttle Program managers and the flight crews, the team accelerated its schedule and delivered a certified EVA IR Camera system in time to support STS-114 in July 2005 as a contingency. The development of the camera system, led by LaRC, was based on the Commercial-Off-the-Shelf (COTS) FLIR S65 handheld infrared camera. An assessment of the S65 system in regards to space-flight operation was critical to the project. This paper discusses the space-flight assessment and describes the significant modifications required for EVA use by the astronaut crew. The on-orbit inspection technique will be demonstrated during the third EVA of STS-121 in September 2005 by imaging damaged RCC samples mounted in a box in the Shuttle's cargo bay.
This study presents Tug Fleet and Ground Operations Schedules and Controls plan. This plan was developed and optimized out of a combination of individual Tug program phased subplans, special emphasis studies, contingency analyses and sensitivity analyses. The subplans cover the Tug program phases: (1) Tug operational, (2) Interim Upper Stage (IUS)/Tug fleet utilization, (3) and IUS/Tug payload integration, (4) Tug site activation, (5) IUS/Tug transition, (6) Tug acquisition. Resource requirements (facility, GSE, TSE, software, manpower, logistics) are provided in each subplan, as are appropriate Tug processing flows, active and total IUS and Tug fleet requirements, fleet management and Tug payload integration concepts, facility selection recommendations, site activation and IUS to Tug transition requirements. The impact of operational concepts on Tug acquisition is assessed and the impact of operating Tugs out of KSC and WTR is analyzed and presented showing WTR as a delta. Finally, cost estimates for fleet management and ground operations of the DDT&E and operational phases of the Tug program are given.
A set of viewgraphs on managing temporal relations in the MAESTRO scheduling system are given. The viewgraphs present information on such topics as why scheduling is hard, managing temporal relations, constraints on the placement of a single activity, constraints between activities, soft constraints (such as preferences), and contingency handling.
The need for improving load shedding on board the space station is one of the goals of aerospace power system automation. To accelerate the optimum load-shedding functions, several constraints must be involved. These constraints include congestion margin determined by weighted probability contingency, component/system reliability index, generation rescheduling. The impact of different faults and indices for computing reliability were defined before optimization. The optimum load schedule is done based on priority, value and location of loads. An optimization strategy capable of handling discrete decision making, such as Everett optimization, is proposed. We extended Everett method to handle expected congestion margin and reliability index as constraints. To make it effective for real time load dispatch process, a rule-based scheme is presented in the optimization method. It assists in selecting which feeder load to be shed, the location of the load, the value, priority of the load and cost benefit analysis of the load profile is included in the scheme. The scheme is tested using a benchmark NASA system consisting of generators, loads and network.