Evaluation of the mathematical and economic basis for conversion processes in the LEAP energy-economy model

An evaluation was made of the mathematical and economic basis for conversion processes in the LEAP energy-economy model. Conversion processes are the main modelling subunit in LEAP used to represent energy conversion industries and are supposedly based on the classical economic theory of the firm. The study arose out of questions about the uniqueness and existence of LEAP solutions and their relation to classical equilibrium economic theory. An analysis of classical theory and LEAP model equations was made to determine their exact relationship. The conclusions drawn from this analysis were that LEAP theory is not consistent with the classical theory of the firm. Specifically, the capacity for factor formalism used by LEAP does not support a classical interpretation in terms of a technological production function for energy conversion processes. The economic implications of this inconsistency are suboptimal process operation and short term negative profits in years where plant operation should be terminated. A new capacity factor formalism, which retains the behavioural features of the original model, is proposed to resolve these discrepancies.     

上海市工业废水排放量的多元非线性回归预测

根据2000年至2009年上海市的人均生产总值和工业重复用水量并结合工业废水排放量的资料,构建了一种基于时间序列的多元非线性回归预测模型,并进行了评估和分析.模型具有较高的拟合精度,能客观反映工业废水的排放量,可以为决策者提供参考,提高相关部门的管理水平.     

A Petri net approach to the modelling and analysis of flexible manufacturing systems

In this paper we present an approach for modelling and analyzing flexible manufacturing systems (FMSs) using Petri nets. In this approach, we first build a Petri net model (PNM) of the given FMS in a bottom-up fashion and then analyze important qualitative aspects of FMS behaviour such as existence/absence of deadlocks and buffer overflows. The basis for our approach is a theorem we state and prove for computing the invariants of the union of a finite number of Petri nets when the invariants of the individual nets are known. We illustrate our approach using two typical manufacturing systems: an automated transfer line and a simple FMS.A shorter version of this paper was presented at the 1st ORSA/TIMS Special Interest Conference on FMSs, University of Michigan, Ann Arbor, August 1984.     

A Tractable and Expressive Class of Marginal Contribution Nets and Its Applications

Coalitional games raise a number of important questions from the point of view of computer science, key among them being how to represent such games compactly, and how to efficiently compute solution concepts assuming such representations. Marginal contribution nets (MC‐nets), introduced by Ieong and Shoham, are one of the simplest and most influential representation schemes for coalitional games. MC‐nets are a rulebased formalism, in which rules take the form pattern → value, where “pattern ” is a Boolean condition over agents, and “value ” is a numeric value. Ieong and Shoham showed that, for a class of what we will call “basic” MC‐nets, where patterns are constrained to be a conjunction of literals, marginal contribution nets permit the easy computation of solution concepts such as the Shapley value. However, there are very natural classes of coalitional games that require an exponential number of such basic MC‐net rules. We present read‐once MC‐nets, a new class of MC‐nets that is provably more compact than basic MC‐nets, while retaining the attractive computational properties of basic MC‐nets. We show how the techniques we develop for read‐once MC‐nets can be applied to other domains, in particular, computing solution concepts in network flow games on series‐parallel networks (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

具有特殊坐标曲线网的B\'ezier曲面

在计算机辅助几何设计中, B\''ezier曲面是一类重要的参数曲面.在微分几何中,坐标曲线网也是重要的研究内容.本文中,我们对具有特殊坐标曲线网(如正交曲线网、曲率曲线网、共轭曲线网等)的B\''ezier曲面进行研究.此外,我们还构造了满足能量约束的特殊B\''ezier曲面,给出了基于控制结构的充分条件并给出具体实例.     

Optimising cargo loading and ship scheduling in tidal areas

This paper describes a framework that combines decision theory and stochastic optimisation techniques to address tide routing (i.e. optimisation of cargo loading and ship scheduling decisions in tidal ports and shallow seas). Unlike weather routing, tidal routing has been little investigated so far, especially from the perspective of risk analysis. Considering the journey of a bulk carrier between N ports, a shipping decision model is designed to compute cargo loading and scheduling decisions, given the time series of the sea level point forecasts in these ports. Two procedures based on particle swarm optimisation and Monte Carlo simulations are used to solve the shipping net benefit constrained optimisation problem. The outputs of probabilistic risk minimisation are compared with those of net benefit maximisation, the latter including the possibility of a ‘rule-of-the-thumb’ safety margin. Distributional robustness is discussed as well, with respect to the modelling of sea level residuals. Our technique is assessed on two realistic case studies in British ports. Results show that the decision taking into account the stochastic dimension of sea levels is not only robust in real port and weather conditions, but also closer to optimality than standard practices using a fixed safety margin. Furthermore, it is shown that the proposed technique remains more interesting when sea level variations are artificially increased beyond the extremes of the current residual models.     

Dependent interest and transition rates in life insurance

For market consistent life insurance liabilities modelled with a multi-state Markov chain, it is of importance to consider the interest and transition rates as stochastic processes, for example in order to consider hedging possibilities of the risks, and for risk measurement. In the literature, this is usually done with an assumption of independence between the interest and transition rates. In this paper, it is shown how to valuate life insurance liabilities using affine processes for modelling dependent interest and transition rates. This approach leads to the introduction of so-called dependent forward rates. We propose a specific model for surrender modelling, and within this model the dependent forward rates are calculated, and the market value and the Solvency II capital requirement are examined for a simple savings contract.     

Adaptive Modelling,Simulation and Optimization of Gas and Water Supply Networks

We consider the simulation and optimisation of transport processes through gas and water supply networks. Using a consistent modeling of the network, adjoint equations for the whole system including initial, coupling and boundary conditions can be derived. These are suitable to compute gradients for optimization tasks but can also be used to estimate the accuracy of models and the discretization with respect to a given cost functional. We show the applicability of an adaptive algorithm that automatically steers the discretization and models while maintaining a given accuracy in an optimisation framework. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Modelling and simulation of heat exchange and transport in a geothermal plant

The production of energy by use of the high temperature in the earth's mantle has played an increasingly important role in recent years. However, large uncertainties concerning the conditions in the subsurface make it difficult to use power plants efficiently. An appropriate modelling and simulation of the heat exchange and transport provides a promising tool for further investigations of the process and optimisation of the productivity. Starting from the isothermal state at high temperatures, a cold fluid is injected through a borehole into a porous rock by applying a pressure difference between at least two wells. Passing the fractured rock, the water is heated at the crack interfaces. In addition to the convection of the temperature due to the water flow, the conduction of heat in the rock and the water has to be considered. The modelling approach of this coupled process is based on the Theory of Porous Media (TPM). Both, the rock and the water, are assumed to be materially incompressible and the thermal expansion is solely considered for the fluid, since the expansion of the rock is negligible for the occurring temperature differences. Furthermore, it is assumed that the subsurface is saturated with water. To solve the generated initial-boundary-value problem, the governing primary variables of the coupled model are spatially approximated by mixed finite elements and the time discretisation is carried out by an implicit Euler time-integration scheme. Since in the considered problem the convective transport is dominant, a streamline upwinding scheme is used for the numerical stabilisation to obtain non-oscillatory solutions. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Recent applications of CFD modelling in the power generation and combustion industries

Computational fluid dynamics (CFD) modelling is now widely applied as an industrial plant development and process optimisation tool. The steady increase in computer power over recent years has enabled process engineers to model reacting multi-phase flows in a realistic geometry with good mesh resolution. As a result, the number of applications of CFD to industrial processes is also growing rapidly and increasing in sophistication. This paper reviews some of the recent applications of the CFX-4 code [CFX-4.3: Solver Manual, AEA Technology Engineering Software, 1999] to the power generation and combustion industries. The aim is to illustrate what can be done and also to identify trends and those areas where further work is needed. Examples include coal-fired low-NO_x burner design, furnace optimisation, over-fire air, gas reburn, and laminar flames. It is argued that the trend is for CFD models to become more comprehensive and accessible by being coupled to other process models and embedded in automated information and process control systems.     

Uncertainty in energy-economic modelling of the electrical power sector

The purpose of the present paper is to investigate what significance, if any, inclusion of uncertainties has for the conclusions of the modelling and analysis, i.e., whether the policy recommendations implicit in the results of the analysis depend on the inclusion or not of uncertainties. We do this within the context of a model of the Northern European electricity sector. The paper considers uncertainties about future states of nature. More specifically, we consider the inflow of water into a hydropower production system, where the states of nature are represented by a “dry”, a “normal” and a “wet” year. The problems may be formulated as non-linear optimisation models where the objective function basically consists of the expected value of the sum of consumers', producers', and authorities' surplus. The models take into account that there are losses in the transmission and distribution of electricity, and that the consumers pay an energy tax on their use of electricity. The consumers are divided into two groups, households and industry. Also, complementarity formulations are used, as these are shown to be more adequate for certain aspects, in particular where risk aversion within a liberalised market context is modelled. For each of eight Northern European countries, the basic results of the models are the installation of new production capacities, the production on old and new production capacities, the electricity prices, and the interchange between the countries. The investment in new production capacity is represented by a single value for each country, while the productions differ in that they depend on natural phenomena, which we refer to as the state of nature and represent by stochastic variables. It was found that in this context it was relatively easy to include stochastic elements in the model. Second, complementarity formulations are preferable to optimisation based modelling for some problem types. Third, results of the stochastic model have natural interpretations, also compared to one or several versions of a deterministic model. And fourth, we have seen that the quantitative results, and hence the implied policy recommendations, may differ significantly from those of deterministic models. We therefore conclude that increased attention should be given to the inclusion of stochastic elements into the modelling of energy systems. This revised version was published online in June 2006 with corrections to the Cover Date.     

Representation in the (Artificial) Immune System

Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or, modelling biologically plausible dynamical systems, with little overlap between. We propose that this dichotomy is somewhat to blame for the lack of significant advancement of the field in either direction and demonstrate how a simplistic interpretation of Perelson’s shape-space formalism may have largely contributed to this dichotomy. In this paper, we motivate and derive an alternative representational abstraction. To do so we consider the validity of shape-space from both the biological and machine learning perspectives. We then take steps towards formally integrating these perspectives into a coherent computational model of notions such as life-long learning, degeneracy, constructive representations and contextual recognition—rhetoric that has long inspired work in AIS, while remaining largely devoid of operational definition.     

An extended event graph-based modelling method for parallel and distributed discrete-event simulation

The developing logical process (LP)-based parallel and distributed discrete-event simulation (PDES) in the existing PDES programming environments is a difficult and time-consuming process. Event graph is a simple and powerful modelling formalism of discrete-event simulation, whereas this formalism does not support PDES. This article proposes an extension of the event graph to consider the communication of LPs via the events sent, which is called ‘extended event graph (EEG)’, and proposes an EEG-based modelling method for PDES. This modelling method shifts the focus of PDES development from writing code to building models, and the system implementation can be automatically and directly generated from EEG model. The experimental results show that EEG models can successfully execute in the parallel simulator, and this framework can effectively improve the PDES modelling activities.     

An anisotropic enhanced thermal conductivity approach for modelling laser melt pools for Ni-base super alloys

Ni-base super alloys are extensively used in high temperature gas turbine engines and energy industries. Due to the high replacement costs of these components, there are huge economic benefits of repairing these components. Laser direct metal deposition processes (LDMD) based on laser cladding, laser fusion welding, and laser surface melting are some of the processes which are used to repair these high value components. Precise control of these processes is important to achieve the desired microstructure, stress distribution, distortions due to thermal stresses and other important output variables. Modelling of these processes is therefore an extremely important activity for achieving any degree of control/optimisation. However, modelling of these processes is not straight-forward due to melt pool flows dominated by Marangoni and buoyancy driven convection. Detailed CFD models are required for accurate prediction of melt pool geometry. But these models are computationally expensive and require greater expertise. To simplify and speed up the modelling process, many researchers have used the isotropic enhanced thermal conductivity approach to account for melt pool convection. A recent study on mild steel has highlighted that isotropic enhanced thermal conductivity approach is not able to accurately predict the melt pool geometry. Based on these findings a new approach namely anisotropic enhanced thermal conductivity approach has been developed. This paper presents an analysis on the effectiveness of the isotropic and anisotropic enhanced thermal conductivity approaches for laser melting of Inconel 718 using numerical technique. Experimental melt pool geometry has been compared with modelling results. It has been found that the isotropic enhanced thermal conductivity approach is not able to accurately predict the melt pool geometry, whereas anisotropic enhanced thermal conductivity approach gives good agreement with the experimental results.     

Enriched workflow modelling and Stochastic Branch-and-Bound

Workflow systems provide means and techniques for modelling, designing, performing and controlling repetitive (business) processes. The quality of commercial workflow systems is usually determined to a large extent by their versatility and multi-purpose application. One of the current trends in improving workflow systems lies in enriching modelling methods and techniques in order to enlarge design alternatives.The need for such advanced methods is particularly apparent in those fields in which the process duration can be determined only vaguely, but whose completion schedules are at the same time strictly enforced by a highly competitive market by means of fines and penalties. The risk of an overrun has to be weighed against the expected costs and benefits of certain measures reducing turn-around time and their combinations. Because they can help to avoid such penalties—or, at least, keep any potential losses low by identifying critical subprocesses and evaluate appropriate measures—modelling and evaluation techniques are becoming essential features of workflow systems.Methodologically, we use Stochastic Branch-and-Bound as a technique for finding “optimal” bundles of measures. A numerical study shows the benefits of this meta-approach by means of five stepwise-developed decision scenarios requiring rich modelling. Petri nets as a modelling tool and Stochastic Branch-and-Bound as an optimization technique determine for multi-mode resource constrained workflows of varying complexity an optimal workforce strategy with respect to the number of workers and their qualification.     

Closed nets in linear groups

The paper reviews the author’s results in the theory of elementary nets (carpets). In particular, closed (admissible) nets are investigated. For an elementary net (a net considered without the diagonal) of additive subgroups of an arbitrary commutative ring, the concepts of the derivative net, the closure of the net, and the net associated with the elementary group are introduced. Factorization of the elementary groups is proposed. This factorization is then used to construct an example of a closed (admissible) net which cannot be completed to a (complete) net. For a third-order elementary net σ of additive subgroups of a commutative ring, decomposition of an elementary transvection from the elementary group E(σ) is obtained.     

Energy models for decision making

Since the 1973 oil crisis there has been an explosion in energy modelling activities throughout the world. A bewildering array of models have been or are being developed. The models differ in their geographical scope (local, national, regional or global), their technical scope (a process, an industry, an energy source or all energy industries), their timescale (one to one hundred years) and their systems boundaries (energy, economy, society). In addition there are crucial differences in the level of detail modelled, in the way time is structured and in the way in which decisions are included or perhaps excluded from the model.The natural questions to ask are what sort of models are now available; which models are suitable for which purposes; what has been learnt so far; which are the promising directions for future developments? This paper draws on modelling experience both within the National Coal Board and elsewhere to discuss these questions. The paper contains the following sections: energy models and decision making processes; choosing model boundaries; logic and facts, the basis of the model; choice of energy model; links to the economy; future directions. The subject will be of interest to specialist energy modellers and those interested more generally in strategic modelling for government and industry.     

Petri net modelling of biological regulatory networks

The complexity of biological regulatory networks often defies the intuition of the biologist and calls for the development of proper mathematical methods to model their structures and to delineate their dynamical properties. One qualitative approach consists in modelling regulatory networks in terms of logical equations (using either Boolean or multi-level discretisations). The Petri Net (PN) formalism offers a complementary framework to analyse the dynamical behaviour of large systems, either from a qualitative or from a quantitative point of view.

Our proposal consists in articulating the logical approach with the PN formalism. In a previous work, we have already defined a systematic re-writing of Boolean regulatory models into a standard PN formalism. In this paper, we propose a rigorous and systematic mapping of multi-level logical regulatory models into specific standard Petri nets, called Multi-level Regulatory Petri Nets (MRPNs). We further propose some reduction strategies. Consequently, the resulting models become amenable to the algebraic and computational analyses used by the PN community.

To illustrate our approach, we apply it to a multi-level logical model of the genetic switch controlling the lysis-lysogeny decision in the lambda bacteriophage.     

A comprehensive approach of planning and scheduling based on petri nets

The main results available on the use of black-and-white Petri nets for modelling, planning and scheduling manufacturing systems are presented. In the first part of the paper, the basics of Petri nets necessary to understand the subsequent presentation are introduced. Particular attention is paid to event graphs, a particular type of Petri nets used for modelling and evaluating ratio-driven systems. The second part of the paper is devoted to ratio-driven systems, their modelling and their scheduling. Job-shops, assembly systems, and KANBAN systems are used to illustrate this section. Finally, the general case is investigated of manufacturing systems subject to changing demands. An approach based on conflict-free Petri nets with input and output transitions is proposed for planning and scheduling this type of system.