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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

CLIPS++: Embedding CLIPS into C++

This paper describes a set of C++ extensions to the CLIPS language and their embodiment in CLIPS++. These extensions and the implementation approach of CLIPS++ provide a new level of embeddability with C and C++. These extensions are a C++ include statement and a defcontainer construct; (include (c++-header-file.h)) and (defcontainer (c++-type)). The include construct allows C++ functions to be embedded in both the LHS and RHS of CLIPS rules. The header file in an include construct is the same header file the programmer uses for his/her own C++ code, independent of CLIPS. The defcontainer construct allows the inference engine to treat C++ class instances as CLIPS deftemplate facts. Consequently existing C++ class libraries may be transparently imported into CLIPS. These C++ types may use advanced features like inheritance, virtual functions, and templates. The implementation has been tested with several class libraries, including Rogue Wave Software's Tools.h++, GNU's libg++, and USL's C++ Standard Components. The execution speed of CLIPS++ has been determined to be 5 to 700 times the execution speed of CLIPS 6.0 (10 to 20X typical).

Obermeyer, Lance↗
NASA NTRS1994

CLIPS, AppleEvents, and AppleScript: Integrating CLIPS with commercial software

Many of today's intelligent systems are comprised of several modules, perhaps written in different tools and languages, that together help solve the user's problem. These systems often employ a knowledge-based component that is not accessed directly by the user, but instead operates 'in the background' offering assistance to the user as necessary. In these types of modular systems, an efficient, flexible, and eady-to-use mechanism for sharing data between programs is crucial. To help permit transparent integration of CLIPS with other Macintosh applications, the AI Research Branch at NASA Ames Research Center has extended CLIPS to allow it to communicate transparently with other applications through two popular data-sharing mechanisms provided by the Macintosh operating system: Apple Events (a 'high-level' event mechanism for program-to-program communication), and AppleScript, a recently-released scripting language for the Macintosh. This capability permits other applications (running on either the same or a remote machine) to send a command to CLIPS, which then responds as if the command were typed into the CLIPS dialog window. Any result returned by the command is then automatically returned to the program that sent it. Likewise, CLIPS can send several types of Apple Events directly to other local or remote applications. This CLIPS system has been successfully integrated with a variety of commercial applications, including data collection programs, electronics forms packages, DBMS's, and email programs. These mechanisms can permit transparent user access to the knowledge base from within a commercial application, and allow a single copy of the knowledge base to service multiple users in a networked environment.

Compton, Michael M.↗
NASA NTRS1994

DAI-CLIPS: Distributed, Asynchronous, Interacting CLIPS

DAI-CLIPS is a distributed computational environment within which each CLIPS is an active independent computational entity with the ability to communicate freely with other CLIPS. Furthermore, new CLIPS can be created, others can be deleted or modify their expertise, all dynamically in an asynchronous and independent fashion during execution. The participating CLIPS are distributed over a network of heterogeneous processors taking full advantage of the available processing power. We present the general framework encompassing DAI-CLIPS and discuss some of its advantages and potential applications.

Gagne, Denis↗
NASA NTRS1990

BB-CLIPS: Blackboard extensions to CLIPS

This paper describes a set of extensions made to CLIPS version 4.3 that provide capabilities similar to the blackboard control architecture described by Hayes-Roth. There are three types of additions made to the CLIPS shell. The first extends the syntax to allow the specification of blackboard locations for CLIPS facts. The second implements changes in CLIPS rules and the agenda manager that provide some of the powerful features of the blackboard control architecture. These additions provide dynamic prioritization of rules on the agenda allowing control strategies to be implemented that respond to the changing goals of the system. The final category of changes support the needs of continuous systems, including the ability for CLIPS to continue execution with an empty agenda.

Orchard, Robert A.↗
NASA NTRS1990

A dynamic satellite simulation testbed based on CLIPS and CLIPS-derived tools

We were motivated to define and build a sophisticated satellite simulation capability for the evaluation at a satellite operations automated environment called IntelliSTAR. This architecture, and associated prototype, addresses the entire spacecraft operations cycle including planning, scheduling, task execution, and analysis. It is aimed at increasing the autonomous capability of current and future spacecraft. It utilizes advanced software techniques to address incomplete and conflicting data for making decisions. It also encompasses critical response time requirements, complex relationships among multiple systems, and dynamically changing objectives. Given the extreme scope of activities that are targeted, a sophisticated, flexible, and dynamic simulation environment was required to drive this prototype. In particular the derived requirements for evaluating the IntelliSTAR prototype include realistic and dynamic environment, easily reconfigurable, and multiple levels of fidelity.

Gathmann, Thomas P.↗
DOE OSTI2024

Side-by-Side Comparison of Subhourly Clipping Models

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to sub-hourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of these approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating the Allen and Walker correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons were performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The two models predict annual clipping loss more accurately than simple hourly power limit clipping, with the Allen method typically being slightly more accurate at typical ILR values and the Walker method often being slightly more accurate at high ILR values The models can improve accuracy over the status quo clipping approach up to 3 percentage points in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

ENERGY PLANNING, POLICY, AND ECONOMY,MATHEMATICS A↗
DOE OSTI2024

Side-by-Side Comparison of Subhourly Clipping Models

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to subhourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of these approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating the Allen and Walker correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons were performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The two models predict annual clipping loss more accurately than simple hourly power limit clipping, with the Allen method typically being slightly more accurate at typical ILR values and the Walker method often being slightly more accurate at high ILR values The models can improve accuracy over the status quo clipping approach up to 3 percentage points in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

accuracy↗
DOE OSTI2021

Performance Comparison of Clipping Detection Techniques in AC Power Time Series

In this research, a variety of methods were developed to detect clipping periods in AC power time series. AC power data streams associated with 36 unique systems across the United States were collected, and data points representing clipping periods were manually labeled by experts. Using this data set for training and validation, novel logic-based and machine learning (ML) approaches were developed to classify time series values as clipping or non-clipping. These approaches were compared to the RdTools method for detecting clipping periods. The logic-based and ML XGBoost approaches achieved F-scores of 85.0 and 77.6, respectively, when cross-validated against the manually labeled data, as compared to the current RdTools approach (F-score of 56.4), indicating a significant improvement at detecting clipping periods. Additionally, the effects of each clipping filter when evaluating system degradation rates were assessed, using 31 unique systems across the United States. Results indicate that estimated system degradation rate can vary based on the type of clipping filter used, by up to 0.6% degradation rate for some cases.

clipping↗
NASA NTRS1991

CLIPS: An expert system building tool

The C Language Integrated Production System (CLIPS) is an expert system building tool, which provides a complete environment for the development and delivery of rule and/or object based expert systems. CLIPS was specifically designed to provide a low cost option for developing and deploying expert system applications across a wide range of hardware platforms. The commercial potential of CLIPS is vast. Currently, CLIPS is being used by over 3,300 individuals throughout the public and private sector. Because the CLIPS source code is readily available, numerous groups have used CLIPS as a basis for their own expert system tools. To date, three commercially available tools have been derived from CLIPS. In general, the development of CLIPS has helped to improve the ability to deliver expert system technology throughout the public and private sectors for a wide range of applications and diverse computing environments.

Riley, Gary↗
NASA NTRS1994

MIRO: A debugging tool for CLIPS incorporating historical Rete networks

At the last CLIPS conference, we discussed our ideas for adding a temporal dimension to the Rete network used to implement CLIPS. The resulting historical Rete network could then be used to store 'historical' information about a run of a CLIPS program, to aid in debugging. MIRO, a debugging tool for CLIPS built on top of CLIPS, incorporates such a historical Rete network and uses it to support its prototype question-answering capability. By enabling CLIPS users to directly ask debugging-related questions about the history of a program run, we hope to reduce the amount of single-stepping and program tracing required to debug a CLIPS program. In this paper, we briefly describe MIRO's architecture and implementation, and the current question-types that MIRO supports. These question-types are further illustrated using an example, and the benefits of the debugging tool are discussed. We also present empirical results that measure the run-time and partial storage overhead of MIRO, and discuss how MIRO may also be used to study various efficiency aspects of CLIPS programs.

Tuttle, Sharon M.↗
NASA NTRS1994

Automated rule-base creation via CLIPS-Induce

Many CLIPS rule-bases contain one or more rule groups that perform classification. In this paper we describe CLIPS-Induce, an automated system for the creation of a CLIPS classification rule-base from a set of test cases. CLIPS-Induce consists of two components, a decision tree induction component and a CLIPS production extraction component. ID3, a popular decision tree induction algorithm, is used to induce a decision tree from the test cases. CLIPS production extraction is accomplished through a top-down traversal of the decision tree. Nodes of the tree are used to construct query rules, and branches of the tree are used to construct classification rules. The learned CLIPS productions may easily be incorporated into a large CLIPS system that perform tasks such as accessing a database or displaying information.

Murphy, Patrick M.↗
NASA NTRS1994

CLIPS: The C language integrated production system

Expert systems are computer programs which emulate human expertise in well defined problem domains. The potential payoff from expert systems is high: valuable expertise can be captured and preserved, repetitive and/or mundane tasks requiring human expertise can be automated, and uniformity can be applied in decision making processes. The C Language Integrated Production System (CLIPS) is an expert system building tool, developed at the Johnson Space Center, which provides a complete environment for the development and delivery of rule and/or object based expert systems. CLIPS was specifically designed to provide a low cost option for developing and deploying expert system applications across a wide range of hardware platforms. The commercial potential of CLIPS is vast. Currently, CLIPS is being used by over 5,000 individuals throughout the public and private sector. Because the CLIPS source code is readily available, numerous groups have used CLIPS as the basis for their own expert system tools. To date, three commercially available tools have been derived from CLIPS. In general, the development of CLIPS has helped to improve the ability to deliver expert system technology throughout the public and private sectors for a wide range of applications and diverse computing environments.

Riley, Gary↗
DOE OSTI2021

Validation of Subhourly Clipping Loss Error Corrections

Under-performance of solar PV systems is an important issue that increases risks for stakeholders, including developers, investors and operators. Recently some attention has focused on underestimation of inverter clipping losses as a possible source of over-prediction where sub-hourly solar variability is high. Several models and data sets have been analyzed over the past few years, with the aim of quantifying, predicting, and correcting underestimated clipping loss errors for systems with high DC/AC ratio and solar variability. In this research, we apply a machine learning model developed at NREL to two physical PV systems, to correct for subhourly clipping losses. For each system, we compare overall AC power output for the model taken at 1-minute intervals to AC power output taken at 1-hour intervals with the addition of the subhourly clipping correction. Our findings consistently show that the addition of the clipping loss correction lead to a reduction in mean bias error of 0.8% and 1.2% for systems A and B, respectively, with no additional filtering applied. When examining high solar variability periods where clipping is more pronounced, system A and B experienced a 1.8% and 2.7% reduction in mean bias error, respectively, when the clipping correction was applied.

machine learning↗
DOE OSTI2021

Validation of Subhourly Clipping Loss Error Corrections: Preprint

Under-performance of solar PV systems is an important issue that increases risks for stakeholders, including developers, investors and operators. Recently some attention has focused on underestimation of inverter clipping losses as a possible source of over-prediction where sub-hourly solar variability is high. Several models and data sets have been analyzed over the past few years, with the aim of quantifying, predicting, and correcting underestimated clipping loss errors for systems with high DC/AC ratio and solar variability. In this research, we apply a machine learning model developed at NREL to two physical PV systems, to correct for subhourly clipping losses. For each system, we compare overall AC power output for the model taken at 1-minute intervals to AC power output taken at 1-hour intervals with the addition of the subhourly clipping correction. Our findings consistently show that the addition of the clipping loss correction lead to a reduction in mean bias error of 0.6\% and 1.1\% for systems A and B, respectively, with no additional filtering applied. When examining high solar variability periods where clipping is more pronounced, system A and B experienced a 1.4\% and 2.5\% reduction in mean bias error, respectively, when the clipping correction was applied.

machine learning↗
DOE OSTI2024

Side-by-Side Comparison of Subhourly Clipping Models: Preprint

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to inter-hourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of said approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating two different clipping correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons will be performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The models can improve accuracy up to 3% in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

clipping↗
NASA NTRS1990

CLIPS: A proposal for improved usability

This paper proposes the enhancement of the CLIPS user interface to improve the over-all usability of the CLIPS development environment. It suggests some directions for the long term growth of the user interface, and discusses some specific strengths and weaknesses of the current CLIPS PC user interface. Every user of CLIPS shares a common experience: his/her first interaction with the system itself. As with any new language, between the process of installing CLIPS on the appropriate computer and the completion of a large application, an intensive learning process takes place. For those with extensive programming knowledge and LISP backgrounds, this experience may have been mostly interesting and pleasant. Being familiar with products that are similar to CLIPS in many ways, these users enjoy a relatively short training period with the product. Already familiar with many of the functions they wish to employ, experienced users are free to focus on the capabilities of CLIPS that make it uniquely useful within their working environment.

Patton, Charles R.↗
NASA NTRS1990

HyperCLIPS: A HyperCard interface to CLIPS

HyperCLIPS combines the intuitive, interactive user interface of the Apple Macintosh(TM) with the powerful symbolic computation of an expert system interpreter. HyperCard(TM) is an excellent environment for quickly developing the front end of an application with buttons, dialogs, and pictures, while the CLIPS interpreter provides a powerful inference engine for complex problem solving and analysis. By integrating HyperCard and CLIPS the advantages and uses of both packages are made available for a wide range of uses: rapid prototyping of knowledge-based expert systems, interactive simulations of physical systems, and intelligent control of hypertext processes, to name a few. Interfacing HyperCard and CLIPS is natural. HyperCard was designed to be extended through the use of external commands (XCMDs), and CLIPS was designed to be embedded through the use of the I/O router facilities and callable interface routines. With the exception of some technical difficulties which will be discussed later, HyperCLIPS implements this interface in a straight forward manner, using the facilities provided. An XCMD called 'ClipsX' was added to HyperCard to give access to the CLIPS routines: clear, load, reset, and run. And an I/O router was added to CLIPS to handle the communication of data between CLIPS and HyperCard.

Pickering, Brad↗
NASA NTRS1990

Improving the human factors of software with CLIPS

The use of CLIPS has transformed a conventional graduate course on the human factors of software. Previously, the class centered on lectures and discussions of a mix of ideas for improving the user-friendliness of software. By using CLIPS, the course can focus instead on teaching students to build three rule-based projects in CLIPS for improving the human factors of software. For the first project, students construct a friendly CLIPS front-end to existing software. For the second project students build a CLIPS expert system to help comply with user-interface guidelines. Alternatively, students may build an expert system to assist in detecting discrepancies between user-interfaces and guidelines. For the third project, students use CLIPS to implement a GOMS Model Methodology to assess the human performance impacts of given user-interfaces. Feedback on the projects from the students' colleagues and superiors in the workplace confirm the effectiveness of this CLIPS project-oriented approach to teaching the human factors of user-computer systems. Future refinements are described. Suggestions for those wishing to try this approach are outlined.

Nagy, Thomas J.↗