C. R. Hudson II, Tim Reynolds, G.R. Smolen · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 1981
The PRODCOST computer code simulates the operation of an electric utility generation system. Through a probabilistic simulation the expected energy production, fuel consumption, and cost of operation for each plant are determined. Total system fuel consumption, energy generation by type, total generation costs, as well as system loss of load probability and expected unserved energy are also calculated.
Cited by 1Open access
Mats Jirstrand
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Denis Barthou, Gilbert Grosdidier, K. Petrov et al. · SPIRE - Sciences Po Institutional REpository · 2013
Quantum Chromodynamics (QCD) is the theory of strong nuclear force, responsible of the interactions between sub-nuclear particles. QCD simulations are typically performed through the lattice gauge theory approach, which provides a discrete analytical formalism called LQCD (Lattice Quantum Chromodynamics). LQCD simulations usually involve generating and then processing data on petabyte scale which demands multiple teraflop-years on supercomputers. Large parts of both, generation and analysis, can be reduced to the inversion of an extremely large matrix, the so-called Wilson-Dirac operator. For this purpose, and because this matrix is always sparse and structured, iterative methods are definitely considered. Therefore, the procedure of the application of this operator, resulting in a vector-matrix product, appears as a critical computation kernel that should be optimized as much as possible. Evaluating the Wilson-Dirac operator involves symmetric stencil calculations where each node has 8 neighbors. Such configuration is really hindering when it comes to memory accesses and data exchanges among processors. For current and future generation of supercomputers the hierarchical memory structure make it next to impossible for a physicist to write an efficient code. Addressing these issues in other to harvest an acceptable amount of computing cycles for the real need, which means reaching a good level of efficiency, is the main concern of this paper. We present here a Domain Specific Language and corresponding toolkit, called QIRAL, which is a complete solution from symbolic notation to simulation code.
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Sebastian, Milja, Riya Roy, Sandhra Shaji et al. · Zenodo (CERN European Organization for Nuclear Research) · 2023
Abstract— The field of robotics has advanced significantly in recent years, with the emergence of sophisticated robot sim- ulation and code generation software tools. These tools have revolutionized the way robots are designed, programmed, and deployed in real-world scenarios. This study provides an overview of the various robot simulation and code generation software tools available today, their key features, and their applications in different domains such as manufacturing, healthcare, and agriculture. The study also explores the benefits and challenges of using these software tools, and discusses future directions in this rapidly evolving field. The study could highlight some of the popular robot simulation and code generation software tools such as ROS, Gazebo, V-REP, MATLAB/Simulink, and RobotStudio. It could discuss how these tools can help reduce the time and cost associated with building and testing physical robots by allowing for virtual testing and prototyping. The study could also examinethe role of these tools in facilitating robot-human collaboration, as well as in addressing safety and ethical considerations in robotdesign. The abstract could mention the potential impact of these software tools on the future of robotics, particularly in termsof enabling the development of more intelligent, autonomous,and adaptable robots. Finally, the study could highlight some of the limitations and future research directions for these tools, such as the need for more accurate and realistic simulations, better integration with physical hardware, and improved code optimization techniques.
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Xiaoyan Zhu · 2011
Currently,AADL in mission-critical and safety critical embedded field has a good application.In the design phase,how to simulate AADL model is urgent.Model simulation can iteratively construct and refine design model for early detection of problems,assuring the quality of the design model,thereby reducing the cost of system development.SystemC is a system description language of hardware and software co-simulation.The paper proposed conversion technology and implemented conversion tool for AADL software component to SystemC simulation code.At last,the paper used cruise control system as an example to explain the conversion technology and SystemC-based thread scheduling simulation.Through the research results,users can obtain SystemC-based simulation of AADL software components including the interaction,execution time and sequence between software components,and the thread scheduling simulation,and can implement software and hardware co-simulation through combining AADL hardware component simulation platform.
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Jung, Mooyoung · Scholarworks@UNIST (Ulsan National Institute of Science and Technology) · 1996
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Prashant Shende, Bradley Camburn · arXiv (Cornell University) · 2026
We present a multi-agent framework for generating physics simulation code from natural language descriptions, featuring a novel perceptual self-reflection mechanism for validation. The system employs four specialized agents: a natural language interpreter that converts user requests into physics-based descriptions; a technical requirements generator that produces scaled simulation parameters; a physics code generator with automated self-correction; and a physics validator that implements perceptual self-reflection. The key innovation is perceptual validation, which analyzes rendered animation frames using a vision-capable language model rather than inspecting code structure directly. This approach addresses the ``oracle gap'' where syntactically correct code produces physically incorrect behavior--a limitation that conventional testing cannot detect. We evaluate the system across seven domains including classical mechanics, fluid dynamics, thermodynamics, electromagnetics, wave physics, reaction-diffusion systems, and non-physics data visualization. The perceptual self-reflection architecture demonstrates substantial improvement over single-shot generation baselines, with the majority of tested scenarios achieving target physics accuracy thresholds. The system exhibits robust pipeline stability with consistent code self-correction capability, operating at approximately \$0.20 per animation. These results validate our hypothesis that feeding visual simulation outputs back to a vision-language model for iterative refinement significantly outperforms single-shot code generation for physics simulation tasks and highlights the potential of agentic AI to support engineering workflows and physics data generation pipelines.
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Prashant Shende, Bradley Camburn · arXiv (Cornell University) · 2026
We present a multi-agent framework for generating physics simulation code from natural language descriptions, featuring a novel perceptual self-reflection mechanism for validation. The system employs four specialized agents: a natural language interpreter that converts user requests into physics-based descriptions; a technical requirements generator that produces scaled simulation parameters; a physics code generator with automated self-correction; and a physics validator that implements perceptual self-reflection. The key innovation is perceptual validation, which analyzes rendered animation frames using a vision-capable language model rather than inspecting code structure directly. This approach addresses the ``oracle gap'' where syntactically correct code produces physically incorrect behavior--a limitation that conventional testing cannot detect. We evaluate the system across seven domains including classical mechanics, fluid dynamics, thermodynamics, electromagnetics, wave physics, reaction-diffusion systems, and non-physics data visualization. The perceptual self-reflection architecture demonstrates substantial improvement over single-shot generation baselines, with the majority of tested scenarios achieving target physics accuracy thresholds. The system exhibits robust pipeline stability with consistent code self-correction capability, operating at approximately \$0.20 per animation. These results validate our hypothesis that feeding visual simulation outputs back to a vision-language model for iterative refinement significantly outperforms single-shot code generation for physics simulation tasks and highlights the potential of agentic AI to support engineering workflows and physics data generation pipelines.
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Philipp Herholz, Tuur Stuyck, Ladislav Kavan · ACM Transactions on Graphics · 2024
Optimized parallel implementations on GPU or CPU have dramatically enhanced the fidelity, resolution and accuracy of physical simulations and mesh-based algorithms. However, attaining optimal performance requires expert knowledge and might demand complex code and memory layout optimizations. This adds to the fact that physical simulation algorithms require the implementation of derivatives, which can be a tedious and error-prone process. In recent years, researchers and practitioners have investigated the concept of designing systems that allow for a more expressive definition of mesh-based simulation code. These systems leverage domain-specific languages (DSL), automatic differentiation or symbolic computing to enhance readability of implementations without compromising performance. We follow this line of work and propose a symbolic code generation approach tailored to mesh-based computations on parallel devices. Our system extends related work by incorporating collision handling and a data access synchronization approach, enabling rapid sparse matrix assembly.
Cited by 4Open access
Raoni Sales, Ana Patrícia Fontes Magalhães Mascarenhas, Marco A. C. Simões et al. · Journal of Intelligent & Robotic Systems · 2024
Cited by 2Open access
Ya Qin Chen, Dian Fu, Ying Wang et al. · Applied Mechanics and Materials · 2013
It is crucial for real-time embedded system to design and verify for a little fault may lead to a catastrophe. Architecture Analysis and Design Language (AADL) is a modeling language used to design and analysis the architecture of real-time embedded system based on Model Driven Architecture (MDA). Code generation of AADL model to codes running on the Real-time Operation System can avoid hand-writing mistakes and improve the efficiency of development. Partitioning is introduced into embedded system to control fault transmission. This paper presents a mapping approach to generate codes from AADL model for partitioned system, and the generated codes which include configuration codes and C codes will run on a partitioned platform.
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Andrés Véjar · IFAC Proceedings Volumes · 2009
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Yong-Kun Cheng, Zehong Yu, Zhuo Su et al. · 2024
Simulink has been widely used in embedded software development, which supports simulation to validate the correctness of the constructed models. However, as the scale and complexity of models in industrial applications grow, it is time-consuming for the simulation engine of Simulink to achieve high coverage and detect potential errors, especially accumulative errors.
Cited by 2
Marcello Mura, Maria Giovanna Sami · 2008
Automatic generation of code starting from lightweight modeling languages such as UML is by now a widely adopted approach. In particular generation of executable SystemC models starting from StateCharts and other UML diagrams represents a promising research field. While RTL SystemC appears better suited for matching the StateCharts formalism (being intrinsically clocked), performances of the generated code suffer from the heavy overhead induced by time management, specially when the number of concurrent processes is high. In this paper we present a methodology that allows applying a solution mixing event based and clock-driven approach. More specifically, clock-driven simulation is activated only when the configuration of the system is identified to be evolving. When no events are present this fact is also detected (together with the interval of absence of events) so that no simulation is performed although the clock runs on. This solution is particularly suited for low duty cycle systems, as, e.g. when simulating Wireless Sensor Networks (WSN); in such instances, speedup of the generated code has been found to be well over two orders of magnitude. Application of the technique to the generation of a power simulator for the IEEE 802.15.4 networking protocol is used as a test case.
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R. Nicholas Gerlich · 1997
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N/A · Zenodo (CERN European Organization for Nuclear Research) · 2024
This folder contains the source code of SimGen. Please follow the README for instructions on how to use it
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Deepak Vungarala, Sakila Alam, Arnob Ghosh et al. · 2024
Large Language Models (LLMs) have shown great potential in automating code generation; however, their ability to generate accurate circuit-level SPICE code remains limited due to a lack of hardware-specific knowledge. In this paper, we analyze and identify the typical limitations of existing LLMs in SPICE code generation. To address these limitations, we present SPICEPilot—a novel Python-based dataset generated using PySpice, along with its accompanying framework. This marks a significant step forward in automating SPICE code generation across various circuit configurations. Our framework automates the creation of SPICE simulation scripts, introduces standardized benchmarking metrics to evaluate LLM’s ability for circuit generation, and outlines a roadmap for integrating LLMs into the hardware design process. SPICEPilot is open-sourced under the permissive MIT license at https://github.com/ACADLab/SPICEPilot.git.
Cited by 9
Ramiro Adrián Ghignone, Cristian Federico Falco, Facundo Santiago Larosa et al. · IEEE Latin America Transactions · 2021
Electronic railway interlockings are critical embedded systems which control the safe operation of train signals. Due to the broad variety of railway network topologies and the high functional safety level required, a flexible solution is needed, capable of taking formal requirements and implementing them accordingly to the required application. The scope of this work is to present an approach in which an automatic code generator transforms the control tables which describe the interlocking logic into functional units written in different programming languages like C or VHDL. The generated code allows its implementation in an embedded system based in a FPGA or a microcontroller. In addition, the project contains a graphical user interface to draw and simulate the behavior of the generated model for verification purposes. The developed tool comprises the entire design flow for interlocking systems and presentes several advantages when compared to previous works.
Cited by 6
Lixin chang, Liwen kui · 2021
Model-based design is an effective means for rapid development of embedded software, and automatic code generation is an important technology for model-based development. Combining the automatic code generation method of Matlab and STM32 with the operation and control of the autonomous underwater robot makes the design of the system more convenient. Use tools such as the Simulink library STM32 MAT/Target and STM32 CubeMX of the STM32 microcontroller to realize the automatic generation of readable and portable C code project files. At the same time, based on the design of the model, the control code of the autonomous underwater robot(AUV) is automatically generated, and the control code is added to the automatically generated C code project file. With Matlab/Simulink as the basic software platform, the motion controller of AUV is mounted on the STM32F407, and a real-time simulation system for the closed-loop control of AUV manipulation motion is constructed. The results of the semiphysical real-time simulation test show that the AUV motion controller has good heading depth control performance, realizes the manipulation and control of AUV, and verifies the practicability of the automatically generated code.
Cited by 4
Jingquan Wang, Andrew Negrut, Harry Zhang et al. · Multibody System Dynamics · 2026
Abstract This contribution is concerned with the following issue: can pretrained large language models (LLMs) be refined and customized to the point where they become virtual assistants helping users with the effective use of a simulation tool? In this case study, the “simulation tool” considered is PyChrono, an open source multi-physics dynamics engine for multibody systems. We present a framework for refining and customizing both open- and closed-source LLMs to harness the power of AI in generating scripts that perform PyChrono virtual experiments. We refine and customize several classes of LLMs through a process that leads to a quantifiable improvement in the quality of the generated PyChrono simulation scripts. These scripts can range from simple single-pendulum simulations to complex virtual experiments involving full vehicles on deformable terrain. While the generated scripts are rarely perfect, they often serve as strong starting points for the user to modify and improve on. Additionally, the LLM can answer specific API questions about the simulator, or recommend modeling approaches. The framework discussed is general and can be applied to lower the entry barrier for simulation tools associated with other application domains.
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