Bijective Class of Replicator Equations

Coalescence model of rock-paper-scissors particles

Relatively recent advances in computer technology enable us to create three-dimensional (3D) dynamic models and simulate them within a 3D web environment. The use of such models is especially valuable when teaching simulation, and the concepts behind dynamic models, since the models are made more accessible to the students. Students tend to enjoy a construction process in which they are able to employ their own cultural and aesthetic forms. The challenge is to create a language that allows for a grammar for modeling, while simultaneously permitting arbitrary presentation styles. For further flexibility, we need an effective way to represent and simulate dynamic models that can be shared by modelers over the Internet. We present an Extensible Markup Language (XML)-based framework that will guide a modeler in creating personalized 3D models, visualizing its dynamic behaviors, and simulating the created models. A model author will use XML files to represent geometries and topology of a dynamic model. Model Fusion Engine, written in Extensible Stylesheet Language Transformation (XSLT), expedites the modeling process by automating the creation of dynamic models with the user-defined XML files. Modelers can also link simulation programs with a created model to analyze the characteristics of the model. The advantages of this system lie in the education of modeling and simulating dynamic models, and in the exploitation of visualizing the dynamic model behaviors.

Ageing fields are often in a race against depreciating Net Present Value (NPV) and decreasing production, advent of rising water contacts threatening daily and cumulative production. Static geological models form the primary input model into dynamic models which define and determine the development strategy of fields. Typically, dynamic models built from incipient seismic and geological models comprising of well data from early appraisal wells. In time, incorporation of production data refines the dynamic behaviors of field and in turn, these dynamic models are then used for subsequent re-development of the ageing fields. However, the incipient seismic models rarely receive similar updates as seismic acquisition are too costly to justify in an ageing asset with ever-depreciating NPV. This paper illustrates the process undertaken by subsurface team in identifying potential sites constraints by seismic and geological studies, in comparison with initial oilfield production incorporating pressure data to identify sweep efficiency. Starting with understanding a reservoir that experienced poor injection support, has led to unearthing the presence of faults that were not identified in previous seismic interpretations, and thus compartmentalizing the reservoir. The presence of the ‘unseen’ barriers in between an injector and an oil producer has hampered the injection effort towards the producer, and thus has been detrimental to the health of the reservoir. In lieu of the renewed understanding of the reservoir with regards to field compartmentalization which is recognized as key threat to water injection performance in Reservoir-L, usage of artificial intelligence machine-learning generated fault volumes helped define compartments better. The results indicate the NNW-SSE conjugate (shear) faults formed during the Mid-Late Miocene times which were not clearly demarcated on earlier seismic, play key contributing role with regards to connectivity and intra-field communication. This in turn led to revised understanding on areas of reduced production that led to model updates in line with production behaviors. Based on the new model, well location optimizations were undertaken for two water injectors in the infill drilling campaign for shallower Reservoir-K of Field S to avoid potential compartmentalization that would impact the sweep efficiency. Relocation of the water injectors into the same reservoir compartment as the target oil producer was expected to improve the EUR by ensuring direct sweep and good injectivity to the producer. In summary, by revisiting field models in advent of updating and recalibrating the dynamic model in view of historical production data, the team was able to update the model contributing towards field revitalization and field management in ensuring the field model delivers to the field development plan. The hard work from the team has paid out through the recent production performance of the reservoir.

Traditional games are an important part of Indonesian culture. Traditional games have characteristics and local wisdom of where the game is located. Every traditional game has the same part, namely determining who plays or dividing the players into teams. This preliminary process, which typically involves simple games like rock-paper-scissors or suits, is commonly referred to as ‘hompimpa’. Currently, the popularity of traditional games has declined. To counter the declining popularity of traditional games, this research develops a foundational technology to make them relevant in the digital era. We implement a high-performance object detection model for the hompimpa game, providing a crucial component for future interactive and educational applications aimed at cultural preservation. One of the hompimpa game applied with object detection technology is a rock paper scissors game. This research develops an object detection model using the YOLOv8n architecture and uses the “Rock Paper Scissors SXSW” dataset from Roboflow. From several experiments conducted for model development, the model with 80-epochs is the most optimal model. The 80-epoch model demonstrated strong generalization on an unseen test set, achieving a final mAP@0.5 of 94.8%, a precision of 95.2%, and a recall of 92.1%. Looking at the graph generated in the training process, the 80-epoch model shows no signs of overfitting, enabling it to accurately detect new images.

Hybrid pump-controlled asymmetric cylinder drive systems are implemented for energy saving purposes in applications that do not require fast responses. Under low-velocity and low-pressure conditions, the friction influence in the hybrid pump-controlled system is evident. Researchers have developed various models to describe friction. These friction models are implemented based on the relative motion of the contact surfaces, and they can be categorized into static friction and dynamic friction models. For example, dynamic friction models are suitable for simulating the friction in hydraulic cylinder seals under lubrication conditions. Among the dynamic models, the LuGre model can capture almost all static and dynamic friction behaviors at the macroscopic level; for example, stiction, the Stribeck effect, and hysteresis. Thus, the LuGre model is suitable for describing the friction in hydraulic cylinders. Because the friction force in the hydraulic cylinder is mainly from the cylinder seal and seal deformation occurs under pressure due to its flexibility, the friction in a hybrid pump-controlled hydraulic system is affected by the relative motion of the contact surfaces. Therefore, to investigate factors that affect the friction other than the relative motion of the contact surfaces, the friction behaviors of a hybrid pump-controlled hydraulic system are studied. Pressure difference and acceleration terms are introduced in the LuGre friction model, and the simulated friction results of the updated LuGre model are compared with the measured experimental results to validate the new friction model.

<div class="htmlview paragraph">The purpose of dynamic modeling and simulation of Advanced Life Support (ALS) systems is to help design them. Static steady state systems analysis provides basic information and is necessary to guide dynamic modeling, but static analysis is not sufficient to design and compare systems. ALS systems must respond to external input variations and internal off-nominal behavior. Buffer sizing, resupply scheduling, failure response, and control system design are aspects of dynamic system design. We develop two dynamic mass flow models and use them in simulations to evaluate systems issues, optimize designs, and make system design trades. One model is of nitrogen leakage in the space station, the other is of a waste processor failure in a regenerative life support system.</div> <div class="htmlview paragraph">Most systems analyses are concerned with optimizing the cost/benefit of a system at its nominal steady-state operating point. ALS analysis must go beyond the static steady state to include dynamic system design. All life support systems exhibit behavior that varies over time. ALS systems must respond to equipment operating cycles, repair schedules, and occasional off-nominal behavior or malfunctions. Biological components, such as bioreactors, composters, and food plant growth chambers, usually have operating cycles or other complex time behavior. Buffer sizes, material stocks, and resupply rates determine dynamic system behavior and directly affect system mass and cost. Dynamic simulation is needed to avoid the extremes of costly over-design of buffers and material reserves or system failure due to insufficient buffers and lack of stored material.</div>

As the first step of the development of a computational tool to evaluate the impact resistance of multi-layer coatings, the authors have conducted the formulation of elasto-viscoplastic damage constitutive equation based on continuum damage mechanics and extended to high strain-rate behaviors, the identification of the constitutive modeling based on the tensile test results for each layer material, and its applications to the finite element analysis of tensile fracture behaviors of multi-layer coatings. The obtained results of the identification of constitutive modeling and the tensile fracture analysis have agreed well with the corresponding experimental results. The present dynamic damage mechanics models can be expected to be used as a computational tool for the evaluation and the design of multi-layer coatings.

This paper addresses the kinematic and dynamic modelling and analysis for a robot arm consisting of two hydraulic cylinders driving two revolute joints of the arm. The two cylinders and relevant links of the robot constitute two local closed kinematic chains added to the main robot mechanism. Therefore, the number of the generalized coordinates of the mechanical system is increased, and the mathematical modelling is more complex that requires a formulation of constraint equations with respect to the local closed chains. By using the Lagrangian formulation with Lagrangian Multipliers, the dynamic equations are first derived with respect to all extended generalized coordinates. Then a compact form of the dynamic equations is yielded by canceling the Multipliers. Since the obtained dynamic equations are expressed in terms of independent generalized coordinates which are selected according to active joint variables of the arm, the equations could be best suitable for control law design and implementation. The simulation of the forward and inverse kinematics and dynamics of the arm demonstrates the motion behavior of the robot system.

Nonlinear dynamic modeling and model reduction strategy are studied in this paper for a rotating thin cylindrical shell. The nonlinear dynamic model is first established in terms of ordinary differential equations, in which the effects of Coriolis and centrifugal forces are considered, as well as the initial hoop tension due to rotation. This model describes both the in‐plane vibrations and the flexural vibration and reflects the coupling effects of those deformations. Based on this original model, a novel model reduction strategy is proposed to reduce the degrees of freedom by neglecting vibration modes predominated by in‐plane vibrations. Meanwhile, for the reduced‐order model, the in‐plane vibrations’ contributions to the rotating shell’s response are still preserved. To validate the dynamic model and the model reduction strategy, comparisons and simulations are carried out. Subsequently, nonlinear dynamic behaviors are investigated preliminarily by analyzing the rotating cylindrical shell’s amplitude‐frequency responses under different excitation levels.

A mechanical-magnetic-electro bidirectional coupled dynamic model of a composite cantilever with magnetostrictive shunt damper is established, and the system's transfer functions and a key impedance impact factor are derived. For shunt vibration damping, H2 optimization criterion and the Nelder-Mead search method are used to obtain the optimal parameters of three circuits: resistance shunt (RS), capacitance shunt (CS), and resistance-CS (RCS). Comparisons between the calculated and measured results show that the proposed model can accurately describe the transmissibility vibration frequency responses of the system under RS and CS, and can predict the changing laws of the resonant frequency and the resonant peak with the shunt impedance. It is found that the RCS with negative shunt resistance can provide the peak attenuation rate 90.78%, which is higher than 70.44% of CS and 53.29% of RS, and has wider frequency broadband and faster vibration damping performances than CS and RS.

This paper describes a dynamic heterogeneous one-dimensional model of trickle-bed reactors used for catalytic hydrotreating of oil fractions. The model considers the main reactions in the hydrotreating process of oil fractions: hydrodesulfurization, hydrodenitrogenation, and hydrodearomatization. The dynamic model was first validated using experimental data obtained in an isothermal pilot reactor during hydrotreating of vacuum gas oil over a commercial NiMo catalyst. Then, the model was applied to predict the dynamic behavior of a commercial hydrotreating reactor. Changes in concentration, partial pressure, and temperature profiles are obtained and discussed as a function of reactor axial position and time. The simulations obtained with the proposed dynamic model showed good agreement with experimental data.

A dynamic fundamental model was developed linking processes from the microscopic scale to the equipment scale for batch froth flotation. State estimation, fault detection, and disturbance identification were implemented using the extended Kalman filter (EKF), which reconciles real-time measurements with dynamic models. The online measurements for the EKF were obtained through image analysis of froth images that were captured and analyzed using the commercial package VisioFroth (Metsor Minerals). The extracted image features were then correlated to recovery using principal component analysis and partial least squares regression. The performance of real-time state estimation and fault detection was validated using batch flotation of pure galena at various operating conditions. The image features that were strongly representative of recovery were identified, and calibration and validation were performed against off-line measurements of recovery. The EKF successfully captured the dynamics of the process by updating the model states and parameters using the online measurements. Finally, disturbances in the air flow rate and impeller speed were introduced into the system, and the dynamic behavior of the flotation process was successfully tracked and the disturbances were identified using state estimation.

As the main cause of large blackouts, understanding the complex interactions involved in cascading failure propagation is a critical area of ongoing research. The static model of cascading failures is a well-accepted method to investigate the cascading effects in power systems. However, as the power system evolves, dynamic behaviours become more variable, it is necessary to evaluate the validity of the assumptions in the static model. This paper compares and validates a conventional static model with a novel dynamic model capturing frequency dynamics. N-2 contingency analysis is used to trigger cascading events and the unserved demand and the number of branch outages are used as metrics. Analysis using the 39-bus, 200-bus and 2000-bus benchmark systems reveal similarities and differences between the static and dynamic models and reveal, for the first time, how these differences vary as network size grows. Sensitivity analysis on system dispatch capabilities provides some initial guidance to help reduce the differences between models and helps with understanding of the relative importance of cascading mechanisms.

In the present work mathematical modeling of a CHP system based on Micro Gas Turbine (MGT) with Inverted Brayton Cycle (IBC) (also known as subatmospheric) is provided. Nominal electric power of the facility is 10 kW. Engineering calculation based modeling is conducted to determine optimal parameters of each component, electrical and total efficiency at full load. Further dynamic modeling is provided for the components with determined optimal parameters. With chosen optimal parameters of the scheme components and coolant temperature the dynamic (time-dependent) modeling of disturbance from the nominal state with no control, ramp down and ramp up of power load (a) and heat load (b) with the activated control system was provided. An iteration based approach of MGT modeling is suggested. The difficulties in the system control under reduction of heat consumption are revealed and challenged. The final objectives of the research are comparison of the IBC with the conventional Brayton cycle for MGT application from the electric efficiency, dynamic behavior and controllability points of view, creation of the control system for such a facility.

A full-field dynamic simulation model has traditionally been seen as the benchmark for assimilating all available static and dynamic data to develop robust production forecasts. Santos’ experience modelling the Walloon Coal Measures in its Surat Basin acreage has shown that the performance of individual wells producing from this CSG reservoir is governed by reservoir variability at a fine-scale. This presents a fundamental challenge in developing full-field dynamic models that can accurately describe and predict production performance down to the scale of individual coal seams. Current Queensland CSG projects have focussed on the most prospective acreage, however as subsequent developments move to more marginal areas a greater understanding of the subsurface will be required for optimum development. The target formations will increase in geological complexity, such as Santos’ Surat Basin acreage on the edge of the CSG fairway. Here wells produce from a greater number of distinct coal reservoir units, and how these reservoir units are structured and relate to each other governs reservoir connectivity and defines long-term production performance. Each reservoir unit is comprised of multiple coal plies, all with their own unique maceral distribution and cleating characteristics. These fine-scale properties define the reservoir's dynamic behaviour, and can be impossible to upscale such that these characteristics are preserved at a coarse scale. Consequently, accurately modelling individual well performance will require a fine-scale model to capture and characterise this variability. In development areas where the quantity and quality of reservoir data gathered from exploration and appraisal is sparsely populated, these fine-scale models will need to be populated geostatistically. Without model-scale appropriate control data from production and pressure measurement in the development wells to provide constraints however, a probabilistic model will not accurately define fine-scale behaviour of specific reservoir units. These data requirements can help shape the appraisal scope for new areas and define an appropriate level of surveillance for producing assets. Traditional full-field dynamic modelling has fundamental limitations for interrogating complex unconventional CSG reservoirs at a fine scale. Because of this, alternative workflows are required to answer the subsurface questions necessary to develop CSG assets such as the Surat Basin effectively. This paper details a selection of workflows explored to address this pragmatically, as well as their limitations and associated data requirements. This will also assist in identifying data gaps needed for optimum reservoir management and to aid in the development of these challenging CSG reservoirs.