Thermo-hydraulic steam pipe models for district heating simulations: Simplifications to balance accuracy and simulation speed

With the increasing complexity of communication infrastructures in the automotive domain, approaches for modeling architectures at a high abstraction level have become mandatory to assist designers in the development process of such networked embedded systems. Simulation of architecture models, early in the design process, is also necessary to detect and fix errors and performance issues. In this context, transaction level modeling approaches, supported by languages like SystemC, represent promising solutions to allow performances of networked architectures to be assessed with a good compromise between accuracy and simulation speed. This article presents the application of a simulation-based approach for performance evaluation of a networked embedded system inspired by the automotive domain. The presented modeling approach is defined to efficiently capture the characteristics of architectures for real-time image processing applications. The originality of this paper concerns the considered case study which corresponds to the modeling of a video transmission system made of three electronic controller units and based on a specific power line communication protocol. Compared with traditional communication protocols used in the automotive domain, power line communication is considered here to improve integration of advanced real-time image processing applications. The created model incorporates the description of the different communication layers involved in the studied distributed architecture. Simulation of the model allows evaluating time properties of the architecture according to the various system parameters. Furthermore, the memory cost inferred is also evaluated. Architecture parameters can then be correctly tuned to fully meet the expected requirements.

To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing attention has been directed toward synaptic plasticity. In particular spike-timing-dependent plasticity (STDP) creates specific demands for simulations of spiking neural networks. On the one hand a high temporal resolution is required to capture the millisecond timescale of typical STDP windows. On the other hand network simulations have to evolve over hours up to days, to capture the timescale of long-term plasticity. To do this efficiently, fast simulation speed is the crucial ingredient rather than large neuron numbers. Using different medium-sized network models consisting of several thousands of neurons and off-the-shelf hardware, we compare the simulation speed of the simulators: Brian, NEST and Neuron as well as our own simulator Auryn. Our results show that real-time simulations of different plastic network models are possible in parallel simulations in which numerical precision is not a primary concern. Even so, the speed-up margin of parallelism is limited and boosting simulation speeds beyond one tenth of real-time is difficult. By profiling simulation code we show that the run times of typical plastic network simulations encounter a hard boundary. This limit is partly due to latencies in the inter-process communications and thus cannot be overcome by increased parallelism. Overall, these results show that to study plasticity in medium-sized spiking neural networks, adequate simulation tools are readily available which run efficiently on small clusters. However, to run simulations substantially faster than real-time, special hardware is a prerequisite.

The waveform relaxation (WR) technique is used to accelerate the time-domain simulation of high-fidelity models of supercapacitors. Because of their high power density, supercapacitors are suitable energy storage options in electrified transportation fleets and renewable energy systems. Given their fast charging/discharging profile, high-fidelity models, such as transmission-line models or multistage ladder structures, are conventionally adopted for design and simulation purposes. High-fidelity models, that include fast dynamic modes, can slow down the simulation process. This is problematic, in particular, since supercapacitors are parts of a larger, more complex system, e.g., a power train, with a wide dynamic range. In this paper, frequency-domain characterization of a supercapacitor is conducted by the electrochemical impedance spectroscopy. Then, the equivalent multistage ladder model of the supercapacitor is extracted and parameterized. The high-fidelity model is verified by considering the measured charging profile of the supercapacitor. The WR technique, including circuit partitioning and time windowing, is considered for the resulting high-fidelity model. WR results in an order-of-magnitude improvement in simulation speed while maintaining an excellent agreement with the hardware measurement and conventional simulations.

Hot Jupiters are tidally locked gaseous exoplanets with atmospheric circulations dominated by a super-rotating equatorial jet. Their global circulation is often studied with simulations in 3D general circulation models (GCMs). Energy builds up at the smallest scales in these models and must be dissipated. Many models use ‘hyperdiffusion’ for this, which applies a tendency to the prognostic variables based on a high-order Laplacian operator. This removes the unrealistic and unstable build-up of energy at small scales, and ideally does not affect the large-scale circulation. In this study, we show that hyperdiffusion can in fact affect the large-scale circulation of simulations of hot Jupiters. These planets have large velocity gradients, so hyperdiffusion can produce a momentum tendency that may affect the largest scales. We analyse four simulations with different hyperdiffusion parameters in the GCM THOR. These show that hyperdiffusion can affect the atmospheric zonal momentum budget as strongly as the physical forcing. The hyperdiffusion slows down and spreads out the jet, reducing its speed by more than $50{{\ \rm per\ cent}}$ at some levels. We analyse simulations from the GCMs MITgcm and Exo-FMS and compare the effects of their different dissipation methods. The drag on the jet due to hyperdiffusion can be reduced by using a weaker hyperdiffusion coefficient, a higher resolution, or higher order diffusion. We aim to provide a basis for a study to investigate the ‘real’ momentum budget and jet speed of hot Jupiters. This study shows the need to examine long-held modelling assumptions when studying novel exoplanets.

Recent work in biophysical science increasingly focuses on modeling and simulating human biophysical systems to better understand the human physiome. One program to generate such models is insilicoIDE. These models may consist of thousands or millions of components with complex relations. Simulations of such models can require millions of time steps and take hours or days to run on a single machine. To improve the speed of biophysical simulations generated by insilicoIDE, we propose techniques for augmenting the simulations to support parallel execution in an MPI-enabled environment. In this paper we discuss the methods involved in efficient parallelization of such simulations, including classification and identification of model component relationships and work division among multiple machines. We demonstrate the effectiveness of the augmented simulation code in a parallel computing environment by performing simulations of large scale neuron and cardiac models.

With the advancement of computational power and modeling techniques, automotive and aerospace companies are beginning to utilize highly detailed models throughout the phases of system design and development. Often these systems consist of highly coupled subsystems that span mechanical, electrical, thermal, hydraulic, and pneumatic energy domains. Highly accurate models are typically developed for each individual subsystem, but are operated in isolation, thus ignoring the coupling between subsystems. This can prevent optimal operation at the system level. For large-scale systems, utilizing high-fidelity subsystem models for entire system simulations can be computationally expensive. As a result, lower fidelity models often replace the high-fidelity models at the expense of simulation accuracy. This paper presents a methodology for dynamically changing the fidelity of component models throughout a simulation to find an optimal balance between simulation speed and accuracy. This strategy is demonstrated for a finite-volume model of a vapor compression system where the model fidelity is based on the number of volumes used for the evaporator. Switched-fidelity modeling is shown to increase simulation speed by 64% from the baseline speed of the high-fidelity model, while reducing accumulated error by 69% for secondary flow exit temperature and 76% for primary flow exit pressure from the baseline of the low-fidelity model.

Modified Hurkx band-to-band-tunneling model for accurate and robust TCAD simulations

The wide use of line-commutated rectifiers (LCRs) in large-scale industrial applications has increased the need for accurate and computationally efficient models in power system simulations. Recently, a reduced-order parametric dynamic phasor (PDP) modeling methodology has been proposed in the literature for efficient transient simulation of the LCRs. This methodology permits large simulation time-steps while retaining the information of harmonics present in AC currents and voltages. In this paper, the performance of reduced-order PDP is investigated for an AC distribution system with LCR loads. The results demonstrate a good reconstruction of both steady-state and transient operation behavior, along with improvements in terms of numerical efficiency and simulation speed.

The SystemC TLM-2.0 standard is widely used in modern electronic system level design for better interoperability and higher simulation speed. However, TLM-2.0 has been identified as an obstacle for parallel SystemC simulation due to the disappearance of channels. Without a containment construct, simulation threads are permitted to directly access data of other modules and that makes it difficult to synchronize such accesses as required by the SystemC execution semantics. In this paper, we propose a compile time approach to statically analyze potential conflicts among threads in SystemC TLM-2.0 loosely- and approximately-timed models. We introduce a new Socket Call Path technique which provides the compiler with socket binding information for precise static analysis. We also propose an algorithm to analyze entangled variable pairs. Experimental results show that our approach is able to support automatically safe parallel simulation of SystemC models with TLM-2.0 Blocking Transport Interface, Direct Memory Interface and Non-blocking Transport Interface, resulting in impressive simulation speeds.

Recent trends in the automotive industry have forced OEMs and suppliers to adopt simulation-driven development processes. To meet the demands of the rapidly changing industry, simulation technologies must innovate to provide faster and accurate simulations of increasingly complex models. In this paper we present a set of technologies that were developed to provide a no-compromise, high fidelity, scalable simulation of heterogeneous functional models. Using our new technology we were able to produce more accurate results in orders of magnitude less time than other frequently used techniques in the industry. The proposed approach to co-simulation allows us to perform functional simulation of full-vehicle without sacrificing the solution accuracy or simulation speed.

This paper introduces a rocket model and discusses the advantages of refining it using a variable-structure approach to remodel critical parts. Both versions of the model are implemented in Modelica and were simulated using Dymola as simulation environment. The DySMo framework, which supports the simulation of variable-structure models in common simulation environments, was used to facilitate the redesign. The general benefits of the variable-structure approach are presented, and on the basis of the rocket model we present that simulation time and the data volume of the simulation can be reduced while maintaining the accuracy of the simulation results. variable-structure modeling, simulation speed, data reduction, reduce equation stiffness, rocket launch

The validation of system models at the transaction-level typically relies on discrete event (DE) simulation. In order to reduce simulation time, parallel discrete event simulation (PDES) can be used by utilizing multiple cores available on today's host PCs. However, the total order of time imposed by regular DE simulators becomes a bottleneck that severely limits the benefits of parallel simulation. In this paper, we present a new out-of-order (OoO) PDES technique for simulating transaction-level models on multicore hosts. By localizing the simulation time to individual threads and carefully handling events at different times, a system model can be simulated following a partial order of time without loss of accuracy. Subject to advanced static analysis at compile time and table-based decisions at run time, threads can be issued early, reducing the idle time of available cores. Our proposed OoO PDES technique shows high performance gains in simulation speed with only a small increase in compile time. Using six embedded application examples, we also show the speed trade-off for multicore PDES based on different multithreading libraries.

GSEIM (General-purpose Simulator with Explicit and Implicit Methods) is a simulation platform for solving ordinary differential equations that arise from a schematic diagram of a system. GSEIM offers a graphical environment based on the GNU Radio package, a C++ solver, a Qt-Python based plotting facility, enabling the user to create and edit reusable system models. MATLAB-Simulink is a graphical programming environment that includes a wide range of libraries for modelling and simulating multi-domain systems, which are extensively used in industry and academia. Both Simulink and GSEIM follow block modelling that can make use of implicit and explicit solvers for numerical simulation of plant and controller models. In this work, time domain simulations of open-loop and closed-loop drives of induction motor and permanent magnet synchronous motor drives are performed using both GSEIM and Simulink. The relevant results of machine variables obtained in GSEIM are first benchmarked with Simulink results, and then their simulation speeds are compared. Identical mathematical equations are used in the model development and simulations are run with similar solver settings. For the examples considered here, it is found that GSEIM simulations run faster by a factor of 2 to 4 than Simulink.

Logic simulation of complex VLSI models is very time consuming. Simulation speed can be increased by model partitioning and assigning the resulting parts to simulator instances which cooperate over a loosely coupled system. We have developed a distributed framework, parallelMAP, that implements a hierarchical model partitioning strategy. It can serve both as production environment in VLSI design and as an experimental test bed for algorithm development. In this paper, we describe the possibilities that parallelMAP offers for the modular construction of partitioning processes, starting from basic sequential and parallel modules. Experimental experiences refer to IBM processor models comprising from 1.5 x 105 to 2.5 x 106 elements at gate level.

Efficient design of multiprocessor system-on-chip (MPSoC) requires early, fast, and accurate performance estimation techniques. In this paper, we present new techniques based on fine-grained code analysis to estimate accurate performance during simulation of MPSoC transaction accurate models. First, a GCC profiling tool is applied in the native simulation process. Based on the profiling result, an instruction analyzer of the target CPU architecture is proposed to analyze the cycle cost of C code under estimation. In addition, a memory analyzer is used to further estimate memory access latency including both instruction/data cache time cost and global memory access cycles. Both data and instruction cache models are proposed to estimate cache miss penalty, and a segment-based strategy is adopted to update the cache models more efficiently. Furthermore, an equalized access model is presented to imitate the memory access behavior of processors for estimating global memory access latency caused by bus contention and memory bandwidth. We have applied these techniques on an H.264 decoder application with different hardware architectures. The experimental results show that applying these techniques can obviously improve estimation accuracy of transaction accurate models close to that of the virtual prototype models, with a tolerable overhead on simulation speed.