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Computer program for retrieving stored data and determining variations in launch vehicle performance as function of mission and vehicle parameters
A six-segment management model is presented, each segment of which represents a major area in a new product development program. The first segment of the model covers integration of specialist engineers into 'systems requirement definition' or the system engineering documentation process. The second covers preparation of five basic types of 'development program plans.' The third segment covers integration of system requirements, scheduling, and funding of specialist engineering activities into 'work breakdown structures,' 'cost accounts,' and 'work packages.' The fourth covers 'requirement communication' by line organizations. The fifth covers 'performance measurement' based on work package data. The sixth covers 'baseline requirements achievement tracking.'
A collection of typical three-body trajectories from the L1 libration point on the sun-earth line to the earth is presented. These trajectories in the sun-earth system are grouped into four distinct families which differ in transfer time and delta V requirements. Curves showing the variations of delta V with respect to transfer time, and typical two and three-impulse primer vector histories, are included. The development of a four-body trajectory optimization program to compute fuel optimal trajectories between the earth and a point in the sun-earth-moon system are also discussed. Methods for generating fuel optimal two-impulse trajectories which originate at the earth or a point in space, and fuel optimal three-impulse trajectories between two points in space, are presented. A brief qualitative comparison of these methods is given. An example of a four-body two-impulse transfer from the Li libration point to the earth is included.
A profile of altitude, airspeed, and flight path angle as a function of range between a given set of origin and destination points for particular models of transport aircraft provided by NASA is generated. Inputs to the program include the vertical wind profile, the aircraft takeoff weight, the costs of time and fuel, certain constraint parameters and control flags. The profile can be near optimum in the sense of minimizing: (1) fuel, (2) time, or (3) a combination of fuel and time (direct operating cost (DOC)). The user can also, as an option, specify the length of time the flight is to span. The theory behind the technical details of this program is also presented.
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IPOST is intended to support many analysis phases, from early interplanetary feasibility studies through spacecraft development and operations. The IPOST output provides information for sizing and understanding mission impacts related to propulsion, guidance, communications, sensor/actuators, payload, and other dynamic and geometric environments. IPOST models three degree of freedom trajectory events, such as launch/ascent, orbital coast, propulsive maneuvering (impulsive and finite burn), gravity assist, and atmospheric entry. Trajectory propagation is performed using a choice of Cowell, Encke, Multiconic, Onestep, or Conic methods. The user identifies a desired sequence fo trajectory events, and selects which parameters are independent (controls) and dependent (targets), as well as other constraints and the coat function. Targeting and optimization is performed using the Stanford NPSOL algorithm. IPOST structure allows sub-problems within a master optimization problem to aid in the general constrained parameter optimization solution. An alternate optimization method uses implicit simulation and collocation techniques.
An analysis and design method is presented for the design of composite sandwich cover panels that includes transverse shear effects and damage tolerance considerations. This method is incorporated into an optimization program called SANDOP (SANDwich OPtimization). SANDOP is used in the present study to design optimized composite sandwich cover panels for transport aircraft wing applications as a demonstration of its capabilities. The results of this design study indicate that optimized composite sandwich cover panels have approximately the same structural efficiency as stiffened composite cover panels designed to identical constraints. Results indicate that inplane stiffness requirements have a large effect on the weight of these composite sandwich cover panels at higher load levels. Increasing the maximum allowable strain and the upper percentage limit of the 0 degree and plus or minus 45 degree plies can yield significant weight savings. The results show that the structural efficiency of these optimized composite sandwich cover panels is relatively insensitive to changes in core density.
On January 14, 2005, ESA's Huygens probe separated from NASA's Cassini spacecraft, entered the Titan atmosphere and landed on its surface. As part of NASA Engineering Safety Center Independent Technical Assessment of the Huygens entry, descent, and landing, and an agreement with ESA, NASA provided results of all EDL analyses and associated findings to the Huygens project team prior to probe entry. In return, NASA was provided the flight data from the probe so that trajectory reconstruction could be done and simulation models assessed. Trajectory reconstruction of the Huygens entry probe at Titan was accomplished using two independent approaches: a traditional method and a POST2-based method. Results from both approaches are discussed in this paper.
The primary purpose of the multiPOST tool is to enable the execution of much larger sets of vehicle cases to allow for broader trade space exploration. However, this exploration is not achieved solely with the increased case throughput. The multiPOST tool is applied to carry out a Design of Experiments (DOE), which is a set of cases that have been structured to capture a maximum amount of information about the design space with minimal computational effort. The results of the DOE are then used to fit a surrogate model, ultimately enabling parametric design space exploration. The approach used for the MAV study includes both DOE and surrogate modeling. First, the primary design considerations for the vehicle were used to develop the variables and ranges for the multiPOST DOE. The final set of DOE variables were carefully selected in order to capture the desired vehicle trades and take into account any special considerations for surrogate modeling. Next, the DOE sets were executed through multiPOST. Following successful completion of the DOE cases, a manual verification trial was performed. The trial involved randomly selecting cases from the DOE set and running them by hand. The results from the human analyst's run and multiPOST were then compared to ensure that the automated runs were being executed properly. Completion of the verification trials was then followed by surrogate model fitting. After fits to the multiPOST data were successfully created, the surrogate models were used as a stand-in for POST2 to carry out the desired MAV trades. Using the surrogate models in lieu of POST2 allowed for visualization of vehicle sensitivities to the input variables as well as rapid evaluation of vehicle performance. Although the models introduce some error into the output of the trade study, they were very effective at identifying areas of interest within the trade space for further refinement by human analysts. The next section will cover all of the ground rules and assumptions associated with DOE setup and multiPOST execution. Section 3.1 gives the final DOE variables and ranges, while section 3.2 addresses the POST2 specific assumptions. The results of the verification trials are given in section 4. Section 5 gives the surrogate model fitting results, including the goodness-of-fit metrics for each fit. Finally, the MAV specific results are discussed in section 6.
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Every well-designed machine goes through the process of cost optimization several times during its design, production and operation. The initial optimizations are done during the early proposal stage of the project when none of the systems have been engineered. When a superconducting radio frequency (SRF) linac is implemented as part of the design, it is often a difficult decision as to the frequency and gradient that will be used. Frequently, such choices are made based on existing designs, which invariably necessitate moderate to substantial modifications so that they can be used in the new accelerator. Thus the fallacy of using existing designs is that they will frequently provide a higher cost machine or a machine with sub-optimal beam physics parameters. This paper describes preliminary results of a new software tool that allows one to vary parameters and understand the effects on the optimized costs of construction plus 10 year operations of an SRF linac, the associated cryogenic facility, and controls, where operations includes the cost of the electrical utilities but not the labor or other costs. It derives from collaborative work done with staff from Accelerator Science and Technology Centre, Daresbury, UK [1] several years ago while they were in the process of developing a conceptual design for the New Light Source project. The initial goal was to convert a spread sheet format to a graphical interface to allow the ability to sweep different parameter sets. The tools also allow one to compare the cost of the different facets of the machine design and operations so as to better understand the tradeoffs.
Automated Design Synthesis (ADS) program is general-purpose numerical optimization program containing wide variety of algorithms. Assumed user prepares analysis problem capable of computing objective function and constraints. Program able to accept as part of input design variable quantities. Optimization process carried out by ADS coupled with user's program. ADS used for constrained and unconstrained function minimization. Solution of general problem separated into three basic levels: Strategy, Optimizer, and One-Dimensional Search. Already significant applications in area of structural synthesis (minimum-weight design).
This user's manual is presented for an aerodynamic optimization program that updates flow variables and design parameters simultaneously. The program was developed for solving constrained optimization problems in which the objective function and the constraint function are dependent on the solution of the nonlinear flow equations. The program was tested by applying it to the problem of optimizing propeller designs. Some reference to this particular application is therefore made in the manual. However, the optimization scheme is suitable for application to general aerodynamic design problems. A description of the approach used in the optimization scheme is first presented, followed by a description of the use of the program.
The aerodynamic optimization program used for wing and fuselage optimization of the High Speed Civil Transport was modified for utilization of multiple processors on parallel processor computers. The modified version uses multiple processors to simultaneously conduct three-dimensional flow solutions of different wing and fuselage geometries for calculations of the gradient functions and for directional searches to minimize an objective function. Demonstrations have shown the parallel program to be useful for coarse grid optimization, however memory problems for processors on the IBM SP2 were encountered when finer grid sizes were used.
Control system optimization hybrid computer program
In order to enhance the resilience of the Nation and its ability to protect itself in the face of natural and human-caused hazards, the ability of the critical infrastructure (CI) system to withstand specific threats and return to normal operations after degradation must be determined. To fully analyze the resilience of a region and the CI that resides within it, both the actual resilience of the individual CI and the capability of the Emergency Services Sector (ESS) to protect against and respond to potential hazards need to be considered. Thus, a regional resilience approach requires the comprehensive consideration of all parts of the CI system as well as the characterization of emergency services. This characterization must generate reproducible results that can support decision making with regard to risk management, disaster response, business continuity, and community planning and management. To address these issues, Argonne National Laboratory, in collaboration with the U.S. Department of Homeland Security (DHS) Sector Specific Agency - Executive Management Office, developed a comprehensive methodology to create an Emergency Services Sector Capabilities Index (ESSCI). The ESSCI is a performance metric that ranges from 0 (low level of capabilities) to 100 (high). Because an emergency services program has a high ESSCI, however, does not mean that a specific event would not be able to affect a region or cause severe consequences. And because a program has a low ESSCI does not mean that a disruptive event would automatically lead to serious consequences in a region. Moreover, a score of 100 on the ESSCI is not the level of capability expected of emergency services programs; rather, it represents an optimal program that would rarely be observed. The ESSCI characterizes the state of preparedness of a jurisdiction in terms of emergency and risk management. Perhaps the index's primary benefit is that it can systematically capture, at a given point in time, the capabilities of a jurisdiction to protect itself from, mitigate, respond to, and recover from a potential incident. On the basis of this metric, an interactive tool - the ESSCI Dashboard - can identify scenarios for enhancement that can be implemented, and it can identify the repercussions of these scenarios on the jurisdiction. It can assess the capabilities of law enforcement, fire fighting, search and rescue, emergency medical services, hazardous materials response, dispatch/911, and emergency management services in a given jurisdiction and it can help guide those who need to prioritize what limited resources should be used to improve these capabilities. Furthermore, this tool can be used to compare the level of capabilities of various jurisdictions that have similar socioeconomic characteristics. It can thus help DHS define how it can support risk reduction and community preparedness at a national level. This tool aligns directly with Presidential Policy Directive 8 by giving a jurisdiction a metric of its ESS's capabilities and by promoting an interactive approach for defining options to improve preparedness and to effectively respond to a disruptive event. It can be used in combination with other CI performance metrics developed at Argonne National Laboratory, such as the vulnerability index and the resilience index for assessing regional resilience.