Unconstrained Dynamic Simulation on Offshore Dual Derrick

Dynamic modelling and simulation of a heated brine spray system

This thesis describes the design and implementation of a new dynamic simulator called DASP. It is a computer program package written in standard Fortran 77 for the dynamic analysis and simulation of chemical plants. Its main uses include the investigation of a plant's response to disturbances, the determination of the optimal ranges and sensitivities of controller settings and the simulation of the startup and shutdown of chemical plants. The design and structure of the program and a number of features incorporated into it combine to make DASP an effective tool for dynamic simulation. It is an equation-oriented dynamic simulator but the model equations describing the user's problem are generated from in-built model equation library. A combination of the structuring of the model subroutines, the concept of a unit module, and the use of the connection matrix of the problem given by the user have been exploited to achieve this objective. The Executive program has a structure similar to that of a CSSL-type simulator. DASP solves a system of differential equations coupled to nonlinear algebraic equations using an advanced mixed equation solver. The strategy used in formulating the model equations makes it possible to obtain the steady state solution of the problem using the same model equations. DASP can handle state and time events in an efficient way and this includes the modification of the flowsheet. DASP is highly portable and this has been demonstrated by running it on a number of computers with only trivial modifications. The program runs on a microcomputer with 640 kByte of memory. It is a semi-interactive program, with the bulk of all input data given in pre-prepared data files with communication with the user is via an interactive terminal. Using the features in-built in the package, the user can view or modify the values of any input data, variables and parameters in the model, and modify the structure of the flowsheet of the problem during a simulation session. The program has been demonstrated and verified using a number of example problems.

Quantitative risk assessment integrated with dynamic process simulation for reactor section in heavy oil desulfurization process

The aim of this paper is to analyze different loss modeling methods for hydrostatic pumps and motors as an input for dynamic system simulation. Using dynamic simulation in an early design phase allows for optimization of driveline, driveline control and working hydraulic within several operating conditions. Using precise loss modeling methods enables prediction of energy consumption and energy losses over various duty cycles. Rising energy costs, enhanced government guidelines and increased environmental awareness require more efficient drive concepts especially in mobile working machines. Because of the complex machine structure with numerous hydraulic power consumers, like driveline, working, steering and braking hydraulic, dynamic system simulation is a need in the early design phase. This paper focuses on partial and full hydrostatic drivelines of mobile working machines which operate mostly on basis of a closed circuit hydrostatic transmission. Hydrostatic power lines connect pump and motor directly without additional losses because of valves or system characteristics. Therefore losses in the hydrostatic units have major relevance for the loss behavior of the hydrostatic transmission. The use of precise loss models is essential for analyzing hydrostatic transmission by means of dynamic system simulation. In the scope of this paper, one physical-empiric and four mathematical loss modeling methods are introduced, investigated and compared. Finally, the most promising modeling method is used for the simulation of a state of the art hydrostatic transmission.

During a well start-up, fluid distribution within the well changes from a segregated phase (gas-oil-water) column to a flowing three phase mixture. For this transition to be successful, the well has to overcome the additional hydrostatic head associated with the phase segregation. Depending on the well trajectory, flowline pressure, reservoir pressure and watercut, the start-up process can be challenging for some wells as an improper bean-up procedure can result in a situation where the pressure driving force across the well is not able to overcome the hydrostatic head imposed by the liquid column. This can result in a failed start-up and, for such wells, a correct bean-up strategy is important to ensure successful start-up. In this study, an integrated dynamic multiphase simulator is used to investigate the flow and pressure transients during the start-up of an inactive horizontal oil well which encountered start-up problems after a well intervention job to shut-off high watercut zones. Sensitivities using dynamic simulations for different start-up procedures showed that the well could be successfully started-up by opening the well at the maximum available beansize and ensuring stable flow thereafter by keeping the bean-back above a threshold beansize. The successful well start-up procedure developed using dynamic simulations was applied in the field and resulted in additional oil production. This study demonstrates the significance of dynamic simulations in optimizing well start-up procedures. In this case, this resulted in major incremental revenue for the operator with more than 1000 BOPD added to overall production. Further, the successful start-up procedure devised using a transient multiphase simulator resorted only to well fluids routing and choke manipulation without the need for expensive rig operations and CAPEX/OPEX expenditure.

Automation of forging processes is important for both safety and efficiency in today's advanced manufacturing operations. This work supports the development of an Intelligent Open Die Forging System which will integrate state-of-the-art modelling techniques, automatic die selection and sequencing, full system dynamic simulation, automatic machine programming and coordination, and sensor-based process control to enable the production of more general and complex workpiece geometries than are achievable using current forging methods. Effective automation of this open die forging system requires the coordination and control of the major system components: press, robot, and furnace. In particular, forces exerted on the robot through its manipulation of the workpiece during forging must be minimized to avoid damage to the manipulator mechanism. In this paper, the application of neural networks for compliance control of the forging robot to minimize these forces is investigated. Effectiveness of the neural network-based compliance control module is evaluated through a full dynamic system simulation, which will later form a central part of the complete Intelligent Forging System. Dynamic simulation of the robot is achieved using an efficient O(N) recursive algorithm, while material flow of the workpiece is modeled with a finite element approach. Simulation and timing results for the complete processing system for a specific open die forging example are presented.

Tube-rupture events in shell and tube heat exchangers can result in significantly high surge pressures. Steady state and dynamic methods can be used to assess the impacts of these events on heat exchanger system piping networks. This paper presents the findings of a set of dynamic surge simulations on the impacts of tube-rupture events in a Propane-Feed Gas Heat Exchanger System. Once adjacent piping design is considered, the Joukowsky formulation-based method is not always appropriate to estimate tube-rupture surge impacts. Dynamic simulations need to be conducted to assess the tube-rupture impact on piping systems due to the surge wave amplification as it is transmitted and reflected in the complex pipe network. For blocked-in (noflow) or isolated systems, properly designed relief mechanisms are required to alleviate the tuberupture resultant pressure build-up.

This paper discusses dynamic modeling and simulation of distributed static compensators (DSTATCOM) in system impact studies involving renewable applications, e.g., wind or solar power plants. Two dynamic simulation models of the DTSTACOM are presented and discussed. Dynamic simulations are presented to show that a reactive compensation system (RCS) assembled with the DSTATCOM as a master controller complies with reactive power, voltage control, and low voltage ride-though requirements for a wind power plant. Benchmark and real system models integrate the mechanically switched capacitors and the wind turbine generator reactive power capability into the total RCS system. The reactive characteristics of the DSTATCOM are also discussed.

<p>Probabilistic seismic hazard assessment (PSHA) is widely used to generate national seismic hazard maps, design building codes for earthquake resilient structures, determine earthquake insurance rates, and in general for the management of seismic risk. However, standard PSHA is generally based on empirical, time-independent assumptions that are simplified and not based on earthquake physics. Physics-based numerical models such as dynamic rupture simulations account for the non-linear coupling of source, path and site effects, which can be significant in their respective contributions depending on the generally complex geological environment (e.g., Wollherr et al., 2019), and could potentially complement standard PSHA. In this study we demonstrate the benefits of such an approach by modeling various rupture scenarios in the complex Húsavík–Flatey fault zone (HFFZ), Northern Iceland. The HFFZ consists of multiple right-lateral strike slip segments distributed across ~100 km. The moment accumulated on the HFF since the last major earthquake in 1872 can result in an earthquake of magnitude 6.8 to 7 (Metzger and Jonsson, 2014) posing a high risk to Húsavík’s community, flourishing tourism and heavy industry.</p><p>We perform high-resolution 3D dynamic rupture simulations using the open-source software SeisSol (www.seissol.org), which can efficiently model spontaneous earthquake rupture across complex fault networks and seismic wave propagation with high order accuracy in space and time. Our models incorporate regional topography, bathymetry, 3D subsurface structure and varying models of the complex fault network while accounting for off-fault damage.</p><p>Synthetic ground motions suggest highly heterogenous radiation patterns and intense localization of shaking in the vicinity of geometric complexities, such as fault bends or rupture transition between segments. In our models, the hypocenter location does not affect the plausible moment magnitude of large events. However, changes in rupture directivity affect the spatial distribution of ground motion significantly.  We run hundreds of dynamic rupture scenarios to generate a physics-based dynamic earthquake catalog of mechanically plausible events. Based on this, we identify a possible maximum magnitude earthquake and generate model-based ground motion prediction equations to complement standard empirical ground motion models. In addition, we use the open-source python code SHERIFs (Chartier et al., 2019) to estimate the likelihood of each rupture event, which is mainly constrained by the fault slip rate estimated and fault-to-fault (f2f) rupture scenarios that are determined by the dynamic simulations. Finally, combining the fault seismic rates and the f2f probabilities with dynamic rupture scenarios and the OpenQuake framework allows us to perform physics-based PSHA for the HFFZ, the largest strike-slip fault in Iceland.</p>

Industrial activities pose various environmental risks, including release of chemicals due to accidental spills. A loss of containment study, a study of the effects of chemical spills, seeks to identity and quantify these risks. This study requires site specific considerations in regard to potential consequences and is further complicated by the effects of natural environmental occurrences such as rain. For this reason, the modelling of site spills provides a means of quantitatively predicting the magnitude of potential discharge from industrial sites to the environment. A dynamic simulation that appropriately describes the pumping and overflow characteristics of a drainage network of rainfall and chemical spill catchments is required.Each loss of containment scenario requires consideration under varying conditions. Amcor Cartonboard – Petrie Mill is the site of interest for this study. It is a large site with a complex drainage network. The activities on this site currently involve the transport and storage of various chemicals across the site. This study aims to simulate the effects of loss of containment for a range of scenarios on this site.Following systematic modelling procedures a catchment and physical tank model was constructed. A dynamic site simulation, consisting of a series of appropriately interconnected catchment and physical tanks has been constructed using the DaeSim modelling environment. Utilizing established risk analysis techniques, the results of the model were used to rank potential risks. The combination of these activities is required to complete a loss of containment study.The procedure used in this study can be applied to other industrial sites. Further work possibilities include catchment hold-up investigations, analysis of system component failures, evaporation of chemicals and water, different chemical properties such as particulate settling and density separation and dynamic flow simulation between catchments and tanks. This further work will enhance the accuracy of the model and therefore the predicted releases. This study provides an opportunity for the mill to be aware of the magnitude of risk, directly reduce risk through infrastructure and procedural changes, and become more aware of residual risks. Modelled showed negligible environmental release’s suggesting that Amcor Cartonboard – Petrie Mill is at very low risk in regards to loss of containment. It has been identified that further layers of model complexity are required to enable more accurate results to be obtained and therefore draw reliable conclusions.

BioTFuel may set up facility at Total site in Dunkerque

In conjunction with choosing the treatment process for the new wastewater treatment plant of Espoo, Finland (400,000 P.E.), Denitrification-Nitrification (DN) and Step-Feed activated sludge processes were compared in terms of required basin volume and consumption of aeration air and methanol. The comparison was made using dynamic process simulation. The advantages of the step-feed process reported in literature – smaller volume required to treat an equal load or ability to treat a higher load in an equal volume – were questioned. In terms of consumables, the two processes were found practically equal. This is, to the best of our knowledge, the first comparison of these process configurations with dynamic simulation.

Neural networks are universal approximators for nonlinear functions. This study aimed to develop an algorithm for functional link artificial neural network (FLANN), and to simulate insect’s food intake dynamics using the algorithm. Complete Matlab codes for FLANN algorithm were given in the paper. Conventional models and FLANN were used to modeling accumulated food intake of the larva of a holometabolous insect, Spodoptera litura. Simulation performance of FLANN was compared against conventional models and sensitivity analysis was conducted on FLANN. The results showed that the FLANN algorithm performed better than conventional models in the simulation of dynamics and temperature–time dependent relationship of larva’s food intake. The conventional models like fractional function, polynomial function, and exponential function were indicated to simulate the food intake dynamics at a higher accuracy but their performances were worse than FLANN. Both multivariate linear regression and trend surface model were used to describe temperature–time dependent relationship of food intake. The overall trend for this relationship could be simulated using these models, however, the simulation accuracy of these models was lower than FLANN. Sensitivity analysis showed that Legendre functions, Chebyshov functions, and trigonometric functions, used as the basis functions in FLANN, yielded better fitness than Laguerre functions and Hermite functions. The mean squared error of simulation using Legendre functions, Chebyshov functions, and trigonometric functions decreased as the increase of the number of these basis functions. Simulation performance also varied with the change of type of nonlinear functions and parameter values in the function. Linear function, negative exponential function and power function were the best nonlinear functions, which yielded more stable outputs as the change of parameter values.

Modeling of CSTR and SPR small-scale isothermal reactors for heavy oil hydrocracking and hydrotreating

The teaching of higher mathematics is fundamentally challenged by its abstract and logical nature, while traditional instructional methods show significant limitations in visualizing and dynamizing core concepts. The rise of artificial intelligence has brought revolutionary breakthroughs to the visualization teaching of higher mathematics, largely due to its powerful capabilities in image generation, natural language interaction, and dynamic simulation. This paper focuses on the application of AI technology in this field and systematically constructs three teaching models, “intelligent diagram generation” “interactive experimental exploration”, and “dynamic process simulation”. These models are supported by in-depth analysis of typical cases such as saddle surfaces, vector fields, and integrals. Furthermore, the paper discusses the theoretical foundations and practical pathways of AI visualization teaching, aiming to provide theoretical guidance for promoting the paradigm shift in higher mathematics education from static abstraction to dynamic intuition.