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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.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Observation model and parameter partials for the JPL VLBI parameter estimation software MASTERFIT-1987

This report is a revision of the document of the same title (1986), dated August 1, which it supersedes. Model changes during 1986 and 1987 included corrections for antenna feed rotation, refraction in modelling antenna axis offsets, and an option to employ improved values of the semiannual and annual nutation amplitudes. Partial derivatives of the observables with respect to an additional parameter (surface temperature) are now available. New versions of two figures representing the geometric delay are incorporated. The expressions for the partial derivatives with respect to the nutation parameters have been corrected to include contributions from the dependence of UTI on nutation. The authors hope to publish revisions of this document in the future, as modeling improvements warrant.

Sovers, O. J.↗
NASA NTRS1991

Observation model and parameter partials for the JPL VLBI parameter estimation software MODEST/1991

A revision is presented of MASTERFIT-1987, which it supersedes. Changes during 1988 to 1991 included introduction of the octupole component of solid Earth tides, the NUVEL tectonic motion model, partial derivatives for the precession constant and source position rates, the option to correct for source structure, a refined model for antenna offsets, modeling the unique antenna at Richmond, FL, improved nutation series due to Zhu, Groten, and Reigber, and reintroduction of the old (Woolard) nutation series for simulation purposes. Text describing the relativistic transformations and gravitational contributions to the delay model was also revised in order to reflect the computer code more faithfully.

Sovers, O. J.↗
NASA NTRS2002

Software Estimates Costs of Testing Rocket Engines

Simulation-Based Cost Model (SiCM) is a computer program that simulates pertinent aspects of the testing of rocket engines for the purpose of estimating the costs of such testing during time intervals specified by its users. A user enters input data for control of simulations; information on the nature of, and activity in, a given testing project; and information on resources. Simulation objects are created on the basis of this input. Costs of the engineering-design, construction, and testing phases of a given project are estimated from numbers and labor rates of engineers and technicians employed in each phase, the duration of each phase; costs of materials used in each phase; and, for the testing phase, the rate of maintenance of the testing facility. The three main outputs of SiCM are (1) a curve, updated at each iteration of the simulation, that shows overall expenditures vs. time during the interval specified by the user; (2) a histogram of the total costs from all iterations of the simulation; and (3) table displaying means and variances of cumulative costs for each phase from all iterations. Other outputs include spending curves for each phase.

Source record↗
NASA NTRS2003

Software Estimates Costs of Testing Rocket Engines

Simulation-Based Cost Model (SiCM), a discrete event simulation developed in Extend , simulates pertinent aspects of the testing of rocket propulsion test articles for the purpose of estimating the costs of such testing during time intervals specified by its users. A user enters input data for control of simulations; information on the nature of, and activity in, a given testing project; and information on resources. Simulation objects are created on the basis of this input. Costs of the engineering-design, construction, and testing phases of a given project are estimated from numbers and labor rates of engineers and technicians employed in each phase, the duration of each phase; costs of materials used in each phase; and, for the testing phase, the rate of maintenance of the testing facility. The three main outputs of SiCM are (1) a curve, updated at each iteration of the simulation, that shows overall expenditures vs. time during the interval specified by the user; (2) a histogram of the total costs from all iterations of the simulation; and (3) table displaying means and variances of cumulative costs for each phase from all iterations. Other outputs include spending curves for each phase.

Smith, C. L.↗
NASA NTRS2015

NASA Software Cost Estimation Model: An Analogy Based Estimation Model

The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K-­ nearest neighbor prediction model performance on the same data set.

Hihn, Jairus↗
NASA NTRS1981

Deep space network software cost estimation model

A parametric software cost estimation model prepared for Deep Space Network (DSN) Data Systems implementation tasks is presented. The resource estimation model incorporates principles and data from a number of existing models. The model calibrates task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit DSN software life cycle statistics. The estimation model output scales a standard DSN Work Breakdown Structure skeleton, which is then input into a PERT/CPM system, producing a detailed schedule and resource budget for the project being planned.

Tausworthe, R. C.↗
NASA NTRS1980

Software cost/resource modeling: Deep space network software cost estimation model

A parametric software cost estimation model prepared for JPL deep space network (DSN) data systems implementation tasks is presented. The resource estimation model incorporates principles and data from a number of existing models, such as those of the General Research Corporation, Doty Associates, IBM (Walston-Felix), Rome Air Force Development Center, University of Maryland, and Rayleigh-Norden-Putnam. The model calibrates task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit JPL software lifecycle statistics. The estimation model output scales a standard DSN work breakdown structure skeleton, which is then input to a PERT/CPM system, producing a detailed schedule and resource budget for the project being planned.

Tausworthe, R. J.↗
NASA NTRS1981

Deep space network software cost estimation model

A parametric software cost estimation model prepared for Jet PRopulsion Laboratory (JPL) Deep Space Network (DSN) Data System implementation tasks is described. The resource estimation mdel modifies and combines a number of existing models. The model calibrates the task magnitude and difficulty, development environment, and software technology effects through prompted responses to a set of approximately 50 questions. Parameters in the model are adjusted to fit JPL software life-cycle statistics.

Tausworthe, R. C.↗
NASA NTRS1984

An approach to software cost estimation

A general procedure for software cost estimation in any environment is outlined. The basic concepts of work and effort estimation are explained, some popular resource estimation models are reviewed, and the accuracy of source estimates is discussed. A software cost prediction procedure based on the experiences of the Software Engineering Laboratory in the flight dynamics area and incorporating management expertise, cost models, and historical data is described. The sources of information and relevant parameters available during each phase of the software life cycle are identified. The methodology suggested incorporates these elements into a customized management tool for software cost prediction. Detailed guidelines for estimation in the flight dynamics environment developed using this methodology are presented.

Mcgarry, F.↗
NASA NTRS2008

Estimating Software-Development Costs With Greater Accuracy

COCOMOST is a computer program for use in estimating software development costs. The goal in the development of COCOMOST was to increase estimation accuracy in three ways: (1) develop a set of sensitivity software tools that return not only estimates of costs but also the estimation error; (2) using the sensitivity software tools, precisely define the quantities of data needed to adequately tune cost estimation models; and (3) build a repository of software-cost-estimation information that NASA managers can retrieve to improve the estimates of costs of developing software for their project. COCOMOST implements a methodology, called '2cee', in which a unique combination of well-known pre-existing data-mining and software-development- effort-estimation techniques are used to increase the accuracy of estimates. COCOMOST utilizes multiple models to analyze historical data pertaining to software-development projects and performs an exhaustive data-mining search over the space of model parameters to improve the performances of effort-estimation models. Thus, it is possible to both calibrate and generate estimates at the same time. COCOMOST is written in the C language for execution in the UNIX operating system.

Baker, Dan↗
NASA NTRS1985

Software Cost-Estimation Model

Software Cost Estimation Model SOFTCOST provides automated resource and schedule model for software development. Combines several cost models found in open literature into one comprehensive set of algorithms. Compensates for nearly fifty implementation factors relative to size of task, inherited baseline, organizational and system environment and difficulty of task.

Tausworthe, R. C.↗
DOE OSTI2016

EPRI Software for Estimating Decommissioning Waste Volumes - 16046

EPRI has adapted computer software that can estimate the volume and activity content of waste resulting from the dismantlement of nuclear facilities. This software, designated as Automatic Estimation of the Radiological Inventory or AERI, was originally developed by Iberdrola for use by ENRESA in Spain. The software estimates the radiological inventory for all the components and civil structures of the plant or other facility that are included in the physical inventory. The radiological inventory shows the internal and external surface contamination, as well as the volumetric contamination. The processes of the software are able to estimate both the specific activity levels (in Bq/g or pCi/g) for each radionuclide and the surface activity (Bq/cm{sup 2} or dpm/100 cm{sup 2}) for components and civil structures located in the radiological areas. AERI allows the user to extrapolate, through a statistical approach, the contamination levels obtained by sampling data in specific components and civil structures to the entire facility. The main benefits and values obtained with AERI are the following: - The radiological inventory of the plant can be obtained from a limited set of radiological sampling data. Using the mathematical models allows for the optimization of the number of sampling and analysis that needs to be done. The uncertainties of the calculations are reduced with more data. The user must balance the level of uncertainty of the calculations and the number of sample data they will use. - The automatic management of radiological data in short computing times allows for the execution of several scenarios in a reasonable time. Therefore, different radioactive waste and decommissioning hypotheses can be tested. For example, inventory and data can be split into two different set. One of them can be used for obtaining radiological inventory for early dismantling (3 years, as example) and the second one for deferred dismantling (25 years.) - The software supports the planning and implementation of decommissioning strategies for nuclear plants. For instance, several decontamination factors can be evaluated, assuming different level for decontamination of materials, and results for materials from several streams and use of different container types may be included in each evaluation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2013

Assuring Software Cost Estimates: Is it an Oxymoron?

The software industry repeatedly observes cost growth of well over 100% even after decades of cost estimation research and well-known best practices, so "What's the problem?" In this paper we will provide an overview of the current state oj software cost estimation best practice. We then explore whether applying some of the methods used in software assurance might improve the quality of software cost estimates. This paper especially focuses on issues associated with model calibration, estimate review, and the development and documentation of estimates as part alan integrated plan.

Hihn, Jarius↗
NASA NTRS2013

Assuring software cost estimates : is it an oxymoron?

The software industry repeatedly observes cost growth of well over 100% even after decades of cost estimation research and well-known best practices, so “What’s the problem?” In this paper we will provide an overview of the current state of software cost estimation best practice. We then explore whether applying some of the methods used in software assurance might improve the quality of software cost estimates. This paper especially focuses on issues associated with model calibration, estimate review, and the development and documentation of estimates as part of an integrated plan.

Hihn, Jairus↗