Building Models Of Systems Research Articles

Workflow automation for combined modeling of buildings and district energy systems

In many urban contexts, energy systems are undergoing fundamental change towards more interconnected system layouts. Appropriate planning tools are necessary to guide this transition towards more energy efficient system designs. Thus, the aim of this paper is to present workflow automation approaches to model buildings and district energy systems for dynamic simulation and integral system analyses. For data collection and management, we use a Geographic Information System coupled with a PostgreSQL database. In this paper, we present the software tools TEASER and uesmodels which use this data to automatically generate dynamic building and district energy system models in the modeling language Modelica.To demonstrate the application of these tools for workflow automation, we analyze a university campus with 39 buildings. In one scenario, an optimization led to an improved heating curve, with which yearly primary energy demand in the model was reduced by 0.9%. In a second scenario, the retrofitting of all building envelopes in the district energy system reduced primary energy demand by 16.0%. These examples showed that the presented approach is suited to evaluate options for improving district energy system, ranging from improved operation to changes in system design, and a combination of both.

Soft Systems Methodologies in Action: Environment, Health & Shanghai’s Elderly

This research explored the perception of elderly citizens in Shanghai about negative health impacts of environmental issues. A soft systems methodology (SSM) framework was employed with methodological tools including rich pictures, workshops, social system model building and comparison of models. We found that among our elderly participants, recent government and media campaigns have created the perception that environmental conditions have improved due to government initiatives. The exception to this view is among the educated participants of the study. This suggests that powers of nested social hierarchies and governmental media control still have a dominant influence on public opinion in Shanghai, creating barriers for citizen recognition and understanding of environmental health issues. Education and open access to information are potential areas for intervention to improve understanding and empowerment in this area.

Haydn Shaughnessy: understanding the shift to the new economy

Purpose – In this interview, author and management consultant Haydn Shaughnessy examines how the concept of ecosystems are transforming segments of the economy. Design/methodology/approach – Shaughnessy is interview by radical management guru Stephen Denning. Findings – Ecosystems of companies linked together for mutual gain are enabling interactions and promoting innovation in all the new economy segments. It is increasingly the innovations and expertise of the ecosystem, not the just the talents and resources of the firm, that are critical to future wealth generation.” Practical implications – The Creative Economy … takes the form of delegation of responsibility to individuals and firms in ecosystems that find ways to cooperate and innovate while taking risks with their time and income.” Originality/value – As an exemplar, explains how Autodesk, a leader in CAD/CAM software and building system modeling, has created a platform where companies in construction and civil engineering can draw on a growing number of apps created by an independent community, a dynamic ecosystem. By having continuous connection and securing continuous feedback, companies like Autodesk are able to provide continuous delivery or continuous updates of their products. You don’t need many people to do ecosystem platform business.

Design and Implementation of Enterprise Invoicing Management System

Enters sells saves themanagement system includes the basic information, stock management, salesmanagement, inventory management, query statistics, system management, andother six most. Database concept design includes entity, the use ofPowerDesigner build system model, etc.; Main form design contains basicinformation module suppliers, add, modify and delete, stock management module,etc.Java and JSP are used in the design of the complete portable networkshopping system .

System/scenario duality—a supporting equivalence

The two well-known strategic toolsets of scenarios and systems thinking possess a structural mutuality. The latter focuses on future states, whereas the former focuses on the mechanisms that create those possible futures. An ensemble of scenarios for strategic use should exhibit a homogeneity in its underlying behavioural assumptions while, self-evidently, illustrating variations on those assumptions in terms of the outcomes captured by the scenarios. Thus, in order to create a suitable scenario ensemble (for strategic hypothesising, assessment of candidate policies, risk appraisal, etc) there needs to exist a stable system assumption common to all of the scenarios. The purpose of this paper is to explore the nature of this duality between coherence in a scenario ensemble and the underlying system representation and to illustrate a procedure for utilising this duality to improve scenario and system model building. This is approached from two directions. First, the contribution of explicit system mechanisms (dominant loops) in characterising and creating coherence in scenario ensembles is discussed. Second, the dual problem, that of the extent to which an existing coherent ensemble of scenarios can throw light on the dominant underlying system assumptions, is explored. The conclusions of the paper are that there is use in mobilising this duality of representation, this being illustrated by a brief, multi-informant case study of the futures of the business school industry of the UK. The explication and analysis of the case study shows the procedure in use.

Design of Third-Order Single-Loop Full Feed-Forward Sigma Delta Modulator

Sigma Delta modulator is widely used in ADC for kinds of micro inertial sensors, Sigma Delta ADC can be easily integrated with digital circuits. It possesses some performances of good linearity and high accuracy, while it has no such strict requirements for the match of device dimensions. In this paper, the design of third-order Sigma Delta modulator with a structure of single-loop full feed-forward is accomplished, meanwhile it uses local feedback for zero optimization to improve the shaping capacity of the modulator noise within the signal bandwidth. The OSR (over-sampling rate) of the modulator is 128 and the signal bandwidth is 10 kHz. By the system model building and simulation in the Simulink of MATALAB, the SNR is 96.3 dB and the ENOB is 15.71 bits. Then the modulator is implemented into transistor-level circuits with 0.5um process, by the simulation in Spectre of Cadence, the SNR is 88.5 dB and the ENOB is 14.41 bits. 搜

基于Android的汽车油耗信息管理系统的UML模型

UML是一种用于构造可视化、文档化的图形建模语言。在需求分析的基础上，对基于Android平台的汽车油耗信息管理应用系统，使用UML建模工具，分别建立了添加加油信息UML模型、添加加油站UML模型、加油信息管理UML模型、油耗统计UML模型等，完成对应用软件的分析与设计，采用Java语言完成对应用软件的开发。对油耗统计提出了基于剩余油量的计算方法，比传统的加油灯计算油耗方法更准确有效。实践表明，UML分析可以有效构建系统模型并提高应用软件的开发效率。 UML is a graphical modeling language for visualized construct and documentation representation. After demand of the function is analyzed, UML models of oil information appending, gas stations appending, oil information management and car oil consumption statistics are founded respectively based on UML tool in the information management system of car oil consumption on Mobile with Android OS. Then analysis and design of the application software are implemented. The application software is developed by using Java. The calculation method of car oil consumption is proposed based on the amount of oil left. It is more accurate and effective than traditional method which is based on oil lamp. The actual system shows that UML could be used to build system models effectively and also could improve the efficiency of application software development.

Simultaneous identification of structural parameters and dynamic input with incomplete output-only measurements

SUMMARY A hybrid heuristic optimization strategy is presented to simultaneously identify structural parameters and, when possible, dynamic input time histories from incomplete sets of output measurements. The proposed strategy combines a novel swarm intelligence algorithm, the artificial bee colony algorithm, with a local search operator, Nelder–Mead simplex method, integrated in a search space reduction approach, so as to improve the convergence efficiency of the overall identification process. Because of the independent nature of the algorithm, a parallel scheme is implemented so as to improve the computational efficiency. If the time histories of the structural response and information about the mass of the structural system are available, then the algorithm can also be used for the identification of the time histories of the dynamic input force through a modified Newmark integration scheme, using the current estimates of the structural parameters. To investigate the applicability of the proposed technique, three numerical examples, two shear-type building models and a coupled building system model under different conditions of data availabilities and noise corruption levels are presented. The results show that the proposed technique is powerful, robust and efficient in the simultaneous identification of the structural parameters and input force even from an incomplete set of noise-contaminated structural response measurements. Copyright © 2013 John Wiley & Sons, Ltd.

Biped Walking Robot Gait Planning Research

This paper uses biped walking robot as the research object, and designs robots original system, based on the requirements of Biped Walking Robot Competition of China. According to the biped walking robots characteristics of multi-joints, many degrees of freedom, multivariable, strong coupling and nonlinearity [, we can build system model using the Denavi - Hartenberg coordinate, describe the system model by the homogeneous coordinate transformation theory, and then plan on system gait based on ZMP stability . Finally, we can solve for the joint trajectory of the system by using computer-aided software.

Research on Deep Seam Floor Water-Bursting Assess System

Deep seam floor water-bursting is a complicate nolinear geomechanics system, whose factors are coupling and influencing each other. By building the asses index system, it gets each factors function of water-bursting. According to the four different grey controlling indexes, the main controlling factors are put forward by the grey correlation calculation and nine factors theory is out. Based on the different weighting methods, the entropy adjusting the ancient is used to ascertain the main factors contribution weights, combined static weight with dynamic weight well, so it can provide the comparably correct result for the mathematics model building and discrimination system development.

Spiegelzymes: Sequence Specific Hydrolysis of L-RNA with Mirror Image Hammerhead Ribozymes and DNAzymes

In this manuscript we describe for the first time mirror image catalytic nucleic acids (Spiegelzymes), which hydrolyze sequence specifically L-ribonucleic acid molecules. The mirror image nucleic acid ribozymes designed are based upon the known hammerhead ribozyme and DNAzyme structures that contain L-ribose or L-deoxyribose instead of the naturally occurring D-ribose or D-deoxyribose, respectively. Both Spiegelzymes show similar hydrolytic activities with the same L-RNA target molecules and they also exhibit extra ordinary stabilities when tested with three different human sera. In this respect they are very similar to Spiegelmers (mirror image aptamers), which we had previously developed and for which it has been shown that they are non-toxic and non-immunogenic. Since we are also able to demonstrate that the hammerhead and DNAzyme Spiegelzymes can also hydrolyze mirror image oligonucleotide sequences, like they occur in Spiegelmers, in vivo, it seems reasonable to assume that Spiegelzymes may in principle be used as an antidote against Spiegelmers. Since the Spiegelzymes contain the same building blocks as the Spiegelmers, it can be expected that they will have similar favorable biological characteristics concerning toxicity and immunogenety. In trying to understand the mechanism of action of the Spiegelzymes described in this study, we have initiated for the first time a model building system with L-nucleic acids. The models for L-hammerhead ribozyme and L-DNAzyme interaction with the same L-RNA target will be presented.

Integrating Analytical Models with Descriptive System Models: Implementation of the OMG SyML Standard for the Tool-specific Case of MapleSim and MagicDraw

The Jet Propulsion Laboratory (JPL) is investing heavily in the development of an infrastructure for building system models using the Systems Modeling Language (SysML). An essential component is a transformation apparatus that permits diverse models to be integrated independently of their nature (e.g. declarative, analytical and statistical). This paper presents one useful case: the integration of analytical models expressed using the Modelica language. Modelica is an open standard, declarative, multi-domain modeling language that allows for complex dynamic systems to be modeled. Maplesoft's MapleSim is one software tool that supports the Modelica language. The tool-neutral specification for the transformation between the languages Modelica and SysML is defined in the SysML-Modelica transformation specification (SyML) standard published by the Object Management Group (OMG). As part of the development efforts, said specification has been implemented using the Query-View- Transformation Operational (QVTO) language. During the process, several critical changes to the current SyML standard were proposed. Furthermore, a number of current limitations related to MapleSim were identified. Despite these issues, a proof-of- concept transformation was successfully implemented. In conclusion, the integration of complex simulation models conforming to the Modelica language with SysML-based system models has shown great promise and is a highly useful tool to support the decision making process in design.

Performance of Artificial Neural Network for Predicting Fermentation Characteristics in Biosurfactant Production by Bacillus subtilis ATCC 6633 using Sugar Cane Molasses

Artificial neural network (ANN) was successfully applied to model fermentation parameters for biosurfactant production by Bacillus subtilis ATCC 6633 using sugar cane molasses. Cell growth and biosurfactant production were monitored along the surface activity of the cell-free broth. Response surface methodology (RSM) as a formal statistical model building system was used for the ANN development. The network predicted biosurfactant concentration was 0.381 g/l which showed almost no differences with the relevant experimental value which obtained according to the RSM arrangement. Furthermore, the ANN surface tension reduction was 30.48 mN/m, which was within 3.24% of the experimental value. Comparisons between RSM and the ANN showed preference of using ANN as complementary to RSM and not as a replacement to it.

The role of model building in problem solving and conceptual change

This study examines the effects of the activity of building systems models for school-based problems on problem solving and on conceptual change in elementary science classes. During a unit on the water cycle in an Asian elementary school, students constructed systems models of the water cycle. We found that representing ill-structured problems as system models improves problem solving as well as creating beneficial conceptual change related to the topic.

Performance evaluation and optimal design of supermarket refrigeration systems with supermarket model “SuperSim”. Part II: Model applications

As described in Part I, the supermarket simulation software “SuperSim” with its integrated refrigeration, building and HVAC system models, can be used to evaluate, compare and optimize alternative supermarket refrigeration systems. In Part II the model was used to evaluate and compare the performance of a CO 2 booster refrigeration system with that of a conventional R404A multiplex system in a supermarket application. Floating head pressure control was implemented for both systems when they were in subcritical cycles. For the CO 2 system, when the system was in transcritical cycle due to higher ambient air temperature, the head pressure was optimized through extensive thermodynamic cycle analysis as a function of ambient air temperature. The performance of the CO 2 booster system in the supermarket was then simulated during a one year period and compared with that of the R404A system. As a result, the system performance will benefit from a lower ambient temperature and a sizeable heat recovery for the CO 2 system.

Spherical harmonic-based random fields based on real particle 3D data: Improved numerical algorithm and quantitative comparison to real particles

The shape of particles often plays an important role in how they are used and in the properties of composite systems in which they are incorporated. When building models of systems that include real particles, it is often of interest to generate new, virtual particles whose 3D shape statistics are based on the 3D shape statistics of a collection of real particles. A previous paper showed mathematically how this can be carried out, but only had a small set of real particle shape data to use and only made a limited amount of qualitative comparisons to the real particle data. The present paper shows how the numerical method used to create virtual particles has been improved and immensely accelerated, allowing the use of large particle datasets. Making use of several large particle shape datasets, the paper confirms that the algorithm creates particles whose statistical shape properties closely match the real particles from which they were generated. Another question that can now be addressed with these larger particle datasets is: how many real particles are enough to be representative of the particle class from which they were drawn? The types of particles analyzed include two size ranges of crushed granite-hornblende rocks, silica sand, calcium carbonate powder, and ground granulated blast furnace slag.

Dynamic modelling of low frequency oscillations in swirl burner/furnace systems using artificial neural networks

AbstractThe present paper is concerned with modelling techniques for combustion excited oscillations in swirl burner/furnace systems (SBF) for control strategy development. Artificial neural networks are used to model the combustion dynamics in an SBF which can be made to oscillate under various conditions. A methodology for building system models is proposed where dynamic flowrate measurements of gas and air are absent, the inputs being pressure time records, measurements of mean gas and air flowrates and geometry of the furnace. The modelling has two objectives: one is to model the system fluctuating pressure frequencies and rms amplitude, which can then be used to build a core stimulation model and the other to model the time domain dynamic response to pressure oscillation. Experiments were undertaken on a 100 kW swirl burner/furnace systems (SBF) test rig. This system could be made to oscillate regularly by parametric changes such as mean equivalence ratio, mean gas and air flowrates and small geometr...

TEXTAL System: Artificial Intelligence Techniques for Automated Protein Model Building

Publisher Summary TEXTAL is a new computer program designed to build protein structures automatically from electron density maps. It uses artificial intelligence (AI) and pattern recognition techniques to try to emulate the intuitive decision making of experts in solving protein structures. TEXTAL can be a great time-saving benefit to crystallographers by automatically building accurate models for electron density maps. TEXTAL is aimed at solving maps in the 2.5–3.5 A range that are just at the range of human interpretability, but in practice, TEXTAL is aimed at solving maps constructed from multiwavelength anomalous dispersion (MAD) data. TEXTAL has the potential to reduce one of the bottlenecks of high-throughput structural genomics. As an automated model-building system, it takes an electron-density map as input and ultimately outputs a protein model (with atomic coordinates). The basic idea behind pattern recognition (at least for supervised learning) is to train the system by giving it labeled examples in several competing categories (such as tanks vs. civilian cars and trucks). Each example is represented by a set of descriptive features, which are measurements derived from the data source that characterize unique aspects of each one (for example, color and size).

The development of subsistence system models for Island Southeast Asia and Near Oceania: The nature and role of arboriculture and arboreal-based economies

Unique arboreal-based subsistence economies emerged in Wallacea, New Guinea and Near Oceania. Initial developments have their roots in the Pleistocene. The developmental history of arboreal-based economies (often called arboriculture) in Southeast Asia and the Pacific is not well understood. A framework of subsistence system diversification in relation to unexploited ecological opportunities is useful for subsistence system model building. The emergence of arboreal-based economies in Island Southeast Asia and Near Oceania has significant implications concerning Pacific prehistory, as Austronesian descendants probably incorporated arboriculture and arboreal resources into their economies and subsequently translocated these to the more distant Pacific islands. The overall framework can be applied to assessing subsistence developments elsewhere.

Teaching Power System Dynamics and Control Using SIMULINK

This paper presents an effective method used at the University of Saskatchewan for teaching power system dynamics and control. This method is based on utilizing SIMULINK in building system models and simulating their behavior. Two examples are detailed to demonstrate how the use of such a method significantly enhances the learning process. Rapid modeling of power system models and subsequent simulation results encourage the student to explore power system behavior under a variety of operating conditions, thus, significantly broadening his knowledge of power system dynamics and control.