Performance Of Mathematical Model Research Articles

Identification and Validation of an Engine Performance Database Model for the Flight Management System

This Paper presents the validation studies results of an engine mathematical performance model identification for flight management system trajectory prediction and optimization applications. The methodology was applied to the Cessna Citation X business aircraft, for which the aircraft flight manual and the flight crew operating manual are available. In addition, another data source based on computerized trajectory was also used to generate several climb and descent flight profiles required in the engine model identification process. To demonstrate and further validate the accuracy of the proposed engine performance model, a level-D research aircraft flight simulator of the Cessna Citation X was used as a reference. According to the Federal Aviation Administration (FAA, AC 120-40B), level D corresponds to the highest qualification level for the flight dynamics and engine modeling. Validation of the methodology was accomplished by comparing the prediction model with a series of flight data collected with the flight simulator for different flight conditions and different flight phases including takeoff, climb, cruise, and idle descent. Comparison results were validated with a tolerance of for each engine performance predicted by the model in terms of fan speed, core speed, thrust, and fuel flow.

Special Issue on The Workshop on MAthematical performance Modeling and Analysis (MAMA 2018)

The complexity of computer systems, networks and applications, as well as the advancements in computer technology, continue to grow at a rapid pace. Mathematical analysis, modeling and optimization have been playing, and continue to play, an important role in research studies to investigate fundamental issues and tradeoffs at the core of performance problems in the design and implementation of complex computer systems, networks and applications.

Development of optimal modes and mathematical models of energy performance of electric steelmaking production

The article deals with the issues of determining the optimal modes of electric steelmaking production on the basis of analysis of the graph of changes in the average power and voltage of the arc furnace in one meltdown cycle. In addition, empirical equations for determining the flow rate and specific energy consumption during the operation of process equipment under normal conditions were obtained for the main equipment of the electric arc-furnace shop using the mathematical method.

Determining Production Systems Performance Metrics Considering Machine Downtime

Abstract The monitoring and control of production system performance is a continuing concern within prioritization and optimization decisions regarding manufacturing systems. There is interest on mathematical models of systems performance that facilitate a straightforward computer implementation of continuous monitoring and improvement of the performance of production systems. In this work, it is considered a multi-state system approach for modeling production manufacturing systems and for measuring its long-term performance. One operational measure used for evaluating the manufacturing systems performance is overall equipment effectiveness. Here, the focus on overall equipment effectiveness is the total stoppage time due to corrective maintenance. This study therefore set out to assess a mathematical modeling approach for evaluating decisions about cost-efficient corrective maintenance. This approach is used for computing the manufacturing system states probability distribution, since calculating the total production cost per unit (total unit cost of production plus total unit cost of maintenance). In order to evaluate the goodness of the mathematical approach, a continuous time Markov chain model and a discrete event simulation model are used, by comparing the values obtained using the three techniques. The results demonstrate the effectiveness of the universal generating function for assessing system performance metrics.

Anaerobic Digestion Model No. 1 (ADM1) for mathematical modeling of full-scale sludge digester performance in a municipal wastewater treatment plant.

Anaerobic digestion of sludge is considered to be one of the most appropriate technologies for energy production via conversion of organic matter into methane containing biogas. Biogas produced by anaerobic digestion of municipal wastewater sludge can be utilized as fuel to offset heat and electricity consumption of wastewater treatment facilities. Modeling can be used effectively to evaluate the impact of different process and operation variables on the performance of the treatment processes including complex ones such as anaerobic digestion. Therefore, the Anaerobic Digestion Model No. 1 (ADM1) was applied in order to evaluate the performance of a full-scale anaerobic sludge digester in this study. With the calibration of the most sensitive parameters used in the ADM1, model outputs corresponded well with the measured data obtained from the operation of the full-scale digester. The model was validated with the data acquired from the same anaerobic digester at a different operation period (360days) and simulation results successfully predicted the digester performance. The overall results of this study demonstrated that the ADM1 can be used as a very useful tool to simulate the digestion of mixed sludge generated from full-scale wastewater treatment plants under mesophilic conditions.

Working Memory Impairment Across Psychotic disorders.

Working memory (WM) has been a central focus of cognitive neuroscience research because WM is a resource that is involved in many different cognitive operations. The goal of this study was to evaluate the clinical utility of WM paradigms developed in the basic cognitive neuroscience literature, including methods designed to estimate storage capacity without contamination by lapses of attention. A total of 61 people with schizophrenia, 49 with schizoaffective disorder, 47 with bipolar disorder with psychosis, and 59 healthy volunteers were recruited. Participants received multiple WM tasks, including two versions each of a multiple Change Detection paradigm, a visual Change Localization paradigm, and a Running Span task. Healthy volunteers performed better than the combined patient group on the visual Change Localization and running span measures. The multiple Change Detection tasks provided mixed evidence about WM capacity reduction in the patient groups, but a mathematical model of performance suggested that the patient groups differed from controls in their rate of attention lapsing. The 3 patient groups performed similarly on the WM tasks. Capacity estimates from the Change Detection and Localization tasks showed significant correlations with functional capacity and functional outcome. The patient groups generally performed in a similarly impaired fashion across tasks, suggesting that WM impairment and attention lapsing are general features of psychotic disorders. Capacity estimates from the Change Localization and Detection tasks were related to functional capacity and outcome, suggesting that these methods may be useful in a clinical context.

On pulsing heating of the heat transfer medium in thermal delivery systems

The questions connected with the influence of pulsed heating of the coolant on the operating efficiency and the parameters of the heat supply systems are considered. When implementing such a method in the heating systems of private residential buildings (houses) «hot water boiler – heat exchangers – living quarters», where the working body (heat carrier) is water, it is necessary, along with maintaining comfortable conditions inside the premises, to create an efficient operating mode with minimizing fuel consumption, which may possibly be mutually exclusive influencing factors. In addition, the theoretical justification of the efficiency of using pulsed heating of heating medium in heating systems of residential buildings is extremely limited in the technical literature, which served to formulate the purpose of this work. To achieve it, a mathematical model of the thermal performance of the individual heating system of the building with pulsed heating of the coolant has been developed. Based on the analysis of the heat carrier heating dynamics equation, the main parameters of impulse heating of a heat supply system of a building are determined, the rational values for the duration of the heat input and the pause between the pulses, and the duty cycle of the pulses, depending on the heating surface of the heating devices in the buildings and the thermal losses to the environment. The essential influence of these functional parameters on the characteristics of the impulse heat supply and the heat carrier heating intensity has been shown. The ranges of the change in the pulse frequency have been determined, within which the pulse mode of heat supply in heating systems can be more effective. The concept has been introduced, by analogy with the regular mode of heating (cooling), the rate of heating (cooling) of the coolant – the rate of change in its temperature

Methanol steam reforming performance optimisation of cylindrical microreactor for hydrogen production utilising error backpropagation and genetic algorithm

To optimise methanol steam reforming performance of cylindrical microreactor for hydrogen production, an error backpropagation algorithm was used to build a mathematical model for reaction performance of different microreactors for hydrogen production. Additionally, a genetic algorithm (GA) was utilised to process the computational model to obtain the optimum reaction parameters. The reliability of optimum reaction parameters of cylindrical microreactor for hydrogen production was verified by experiments. Firstly, take platemicroreactor as an example, the porosity of porous copper fiber sintered sheet (PCFSS), reaction temperature of methanol steam reforming for hydrogen production, injection velocity of the methanol and water mixture, and catalyst loading of PCFSS were considered as input data, whereas methanol conversion was used as output data. The computational model for specific testing system was gained by utilising input and output data from specific testing system to train the mathematical model for different microreactors, combining with matrix laboratory (MATLAB) neural network toolbox and designed MATLAB program. The Emax of 5% for plate microreactor and Emax of 3.2% for cylindrical microreactor verified the good predictive ability and reliability of the computational model for plate and cylindrical microreactor, indicating the reliability and universal applicability of the mathematical model for different microreactors. Secondly, the effects and mechanisms of PPI, reaction temperature, injection velocity, and catalyst loading on methanol conversion were studied, relying on the computational model. Finally, the optimum reaction parameters were acquired using GA, MATLAB neural network toolbox and designed MATLAB program. The validity of the optimum reaction parameters of cylindrical microreactor for hydrogen production was confirmed by experiments. This study provides a feasible method for methanol steam reforming performance optimisation for hydrogen production.

Development of Web-Atlas of Available Wind and Wave Energy in the Coastal Zones of the Russian Seas: Information and Cartographic Support (on the Example of the Black Sea)

According to earlier estimates, the Russian coasts have a high potential of wave and wind energy. At the same time, the use of several types of renewable energy sources (RES) allows us to overcome the inherent drawback–the inhomogeneity in time of the energy flow. Nowadays in Russia and abroad, the results of satellite observations, mathematical modeling and reanalysis data are widely used to assess the potential of wind and wave resources. The maps, the atlases, the databases and other information resources (both printed and electronic) are developed for use in the design, mathematical modeling of the power plants performance on the base of RES including hybrid ones. The paper presents the results of developing a Web Atlas of wave and wind energy for the coastal zone of the seas in the Russian Federation, demonstrates the methods for calculating wave and wind characteristics (SWAN spectral wave model), as well as data sources (wind speed reanalyses NCEP / CFSR and NCEP / CFSv2 for the periods 19792010 and 2011-2016). As the characteristics of the energy potential, mean annual values of the height of significant waves, length, period of waves, flux of wave energy, average specific power of the wind flow are calculated and analyzed. The tools for developing a Web Atlas prototype are discussed in detail. Web Atlas is based on the classical three-tier model which includes a storage subsystem (database server), a subsystem for analyzing and publishing data (directly a GIS server), and a Web application subsystem providing a user interface for interacting with data and mapping services (web server). The implementation of the Web Atlas has been carried out for the Black Sea waters. It is planned to further develop the atlas covering the coastal waters of all the seas of Russia.

A Driving-Gear Dynamic Analysis

A new approach of mechanical driving-gear dynamic analysis, which includes several modelling stages is observed in the article. On the first stage driving-gear is represented in the form of consistently connected rotation bodies. The driving-gear is represented in a graphic kind by means of the marked graph. On the second stage mathematical model of driving-gear performance with using of mnemonic rule is created. Mathematical model of mechanical driving-gear is a system of second-order regular differential equations (RDEs). The system of second-order regular differential equations is transformed into a system of first-order regular differential equations. There is a standard method for writing a higher-order RDE as a system of the first-order RDEs. On the third stage computer model of driving-gear performance using system Mathcad is created and initial data is defined. On the fourth stage the mechanical driving-gear modelling is performed and calculation data in numerical and graphical forms is obtained. This approach provides high level of the driving-gear dynamic analysis, including the received results presentation, which is especially important on the earliest stages of mechanical driving-gear design. The proposed procedure of mechanical driving-gear dynamic analysis using Mathcad software significantly decreases time and working costs on execution of such computations and helps to execute investigations related with changing of driving-gear elements parameters efficiently.

Experimental study and modeling development of pressure drop in concurrent gas-liquid columns with a tridimensional rotational flow sieve tray

A novel column internal is proposed, named the tridimensional rotational flow sieve tray (TRST), which has a three-dimensional hollow structure that can make the gas form two kinds of flow pattern coupled with each other: one is rotational flow and the other is flow through the perforations. Using an air-liquid system, we experimentally measured the pressure drops (dry and wet) when gas-liquid flows concurrently downwards through the TRST. We also examined the effects of gas-liquid flux, various geometric parameters of the TRST (i.e. number of blades, twist angles of the blades, tray heights and sieve hole diameters), tray installation methods (forward and backward) and number of installed trays on the pressure drop. The results indicate that the pressure drop increases with increasing gas-liquid flux, number and twist angles of the blades, but decreases with increasing tray heights and sieve hole diameters. The pressure drop of the tray is largest in backward installation, smaller in first installed location and smallest in forward installation. Compared with other new types of trays, the pressure drop of the TRST is lower and there is a significant resistance performance advantage. In addition, according to the mechanism of gas-liquid flow in the TRST, we established the mathematical model of TRST performance in the range of operating conditions. The fitting values agree well with the experimental values.

Using a mathematical model of motivation, volition, and performance to examine students’ e-text learning experiences

This empirical study used Keller’s (Technol Instr Cogn Learn 16:79–104, 2008b) motivation, volition, and performance (MVP) theory to develop and statistically evaluate a mathematical MVP model that can serve as a research and policy tool for evaluating students’ learning experiences in digital environments. Specifically, it explored undergraduate biology students’ learning and attitudes toward e-texts using a MVP mathematical model in two different e-text environments. A data set (N = 1334) that included student motivation and e-text information processing, frustration with using e-texts, and student ability variables was used to evaluate e-text satisfaction. A regression analysis of these variables revealed a significant model that explained 77% of the variation in student e-text satisfaction in both e-text learning environments. Student motivation and intrinsic cognitive load were positive predictors of student satisfaction, while extraneous cognitive load and student prior knowledge and background variables were negative predictors. Practical implications for e-text learning and generalizability of a mathematical MVP model are discussed.

Freelancing - a new approach on the boundary between fragile and anti-fragile after the 2008 economic crisis

Abstract Approaching freelancing, a topical subject in regards to human resources, especially after the economic crisis of 2008, places emphasis on the main advantages of integrating it in HR activity. The economic crisis has represented a critical moment for Romanian organisations and their HR activity, thus generating a series of negative effects on profit and the employees’ individual performances. Ameliorating these negative effects is the top managers’ task, just as much as it is the HR departments, whose role has evolved towards that of a mediator in charge of creating the most appropriate climate for achieving performance, efficiency and optimal results. In order to propose a healthy implementation process, with a view to indicating the phenomenon subjected to analysis, the first step was to analyze each employee’s individual performance metrics. Then, a mathematical modeling of performance with the human resource was developed, by applying an additional linear model on 4 major tasks of human resources spending and a report on performance was calculated - the cost being connected to implementingfreelancing in HR activity in the marketing department.The present study, therefore, provides a concrete solution to the great challenge found in HR management, which is assuring that there is concordance between making spending in HR as efficient as possible and ensuring a high level of motivation and increasing performance with human resources in the organization.

A hybrid energy storage system with optimized operating strategy for mitigating wind power fluctuations

Abstract A novel method based on hybrid energy storage system (HESS), composed of adiabatic compressed air energy storage (A-CAES) and flywheel energy storage system (FESS), to mitigate wind power fluctuations and augment wind power penetration is proposed in this paper. Wind power fluctuates in different frequencies, mainly divided into low and high frequency, which can be coped with by A-CAES and FESS respectively. To fit with low frequency fluctuation exhibiting large magnitude, A-CAES with multi-operating strategies is first proposed to widen operational ranges. Mathematical model of key components' off-design performance is established. For a 49.5 MW wind farm in China, design and optimization of HESS are comprehensively investigated. More specifically, the selection of A-CAES system's key components, such as compressor and expander, and parameters of them are specified as well as the parameters of FESS. The key operating parameters of the HESS, when integrated with wind plant, are analyzed and the characteristics are revealed. The results indicate that by HESS, wind power with fluctuation within 0–49.5 MW (average 25.55 MW) can be stabilized to a steady electrical power output of 24.18 MW. The loss of wind power is 6.6%, far less than the wind power rejection rate 17.1% in China.

Modeling the adenosine system as a modulator of cognitive performance and sleep patterns during sleep restriction and recovery.

Sleep loss causes profound cognitive impairments and increases the concentrations of adenosine and adenosine A1 receptors in specific regions of the brain. Time courses for performance impairment and recovery differ between acute and chronic sleep loss, but the physiological basis for these time courses is unknown. Adenosine has been implicated in pathways that generate sleepiness and cognitive impairments, but existing mathematical models of sleep and cognitive performance do not explicitly include adenosine. Here, we developed a novel receptor-ligand model of the adenosine system to test the hypothesis that changes in both adenosine and A1 receptor concentrations can capture changes in cognitive performance during acute sleep deprivation (one prolonged wake episode), chronic sleep restriction (multiple nights with insufficient sleep), and subsequent recovery. Parameter values were estimated using biochemical data and reaction time performance on the psychomotor vigilance test (PVT). The model closely fit group-average PVT data during acute sleep deprivation, chronic sleep restriction, and recovery. We tested the model’s ability to reproduce timing and duration of sleep in a separate experiment where individuals were permitted to sleep for up to 14 hours per day for 28 days. The model accurately reproduced these data, and also correctly predicted the possible emergence of a split sleep pattern (two distinct sleep episodes) under these experimental conditions. Our findings provide a physiologically plausible explanation for observed changes in cognitive performance and sleep during sleep loss and recovery, as well as a new approach for predicting sleep and cognitive performance under planned schedules.

Session details: Special Issue on The Workshop on MAthematical performance Modeling and Analysis (MAMA 2017)

Session details: Special Issue on The Workshop on MAthematical performance Modeling and Analysis (MAMA 2017)

On Quantitative Analysis Model for the Dynamics of the Effect of Parental Background on Pupil/Students Performance in Mathematics

In this paper, using ordinary differential equations, mathematical performance model was formulated to study the dynamics of pupil/students’ performance in mathematics as a function of parental background, incorporating a number of environmental factors. The model considered 8 subgroups, which led to derivation of 8-Dimensional dynamic mathematical model for the study of students’ performance in mathematics. Model analysis explored numerical methods and the computational simulations of the model indicated that the proportion of pupil/students’ from parents with probability of transmission of hereditary and acquired intelligence exhibited high performance in the subject. However, under a cozy environmental factors, male pupil/students’ possess more of acquired intelligence in mathematical, whereas, the females exhibited dominance and are sharper via hereditary intelligence. The model therefore, recommended devotion of attention and resources by parents on acquired intelligence of their pupil/students’; as well as both governmental and non-governmental agencies willingness to compliment efforts of parents in the provision of appropriate environment for the enhancement of pupil/students’ performance in mathematics. Furthermore, the optimal control and broader predominant studying parameters for similar model is highly encouraged.

Mathematical modelling and evaluation of performance of cuboid packed-bed devices for chromatographic separations

In a recent paper, box-shaped or cuboid packed bed devices have been proposed as alternative to columns for chromatographic separations. We first propose a mathematical model for residence time distribution in such devices. Based on it, we examine factors likely to affect separation performance, and verify the predictions of our mathematical model by conducting tracer experiments. We then compare the performance of two commercial columns with their respective equivalent cuboid packed-bed devices, i.e. containing the same chromatographic media, and having the same bed-height and bed-volume. Parameters compared include the number of theoretical plates, attributes of flow-through and eluted protein peaks, and resolution in model binary protein separations. For each of these metrics examined, the cuboid packed-bed device outperformed its equivalent commercial column. Other potential advantages likely to be gained from using a cuboid packed-bed instead of a column are elucidated.

Mathematical Modelling of Performance of New Type of Climate Adaptive Building Shell

Authors have developed an idea – a new facade system able to adapt to ambient conditions in order to cut heating demand in winter. The facade is called Passive Heating Facade. The facade extracts ground heat from a shallow depth and consequently the temperature of the facade rises. The heat extraction is ensured by passive mechanisms only so no additional energy is necessary.In this work feasibility of proposed system is assessed by the Computational Fluid Dynamics tool ANSYS CFX 16.2. A mathematical model is also applied to calculate possible heat gains of the Passive Heating Facade. Initial analysis of the simplified mathematical model shows that the proposed system is able to extract ground heat for facade heating purposes. It was calculated that one component of the Passive Heating Facade is able to generate around 45 kWh in one season, however the final design consists of several systems.

0241 2B-ALERT APP AND WEB: TOOLS FOR MEASURING, PREDICTING, AND OPTIMIZING NEUROBEHAVIORAL PERFORMANCE AT INDIVIDUAL AND GROUP-AVERAGE LEVELS

To date, no validated, computer-based tools exist to measure, predict, and optimize neurobehavioral performance due to sleep loss at both individual and group-average levels, while also accounting for the effects of caffeine. We addressed this gap by developing and validating a predictive mathematical model of performance [the unified model of performance (UMP)], and instantiating it into two tools: 1) 2B-Alert App, a smartphone application for real-time, individualized performance prediction and 2) 2B-Alert Web, a Web-based software for designing sleep/wake and caffeine schedules to optimize group-average performance. We developed and validated the UMP on psychomotor vigilance task (PVT) performance data from 14 different studies (in laboratory and field conditions), encompassing >500 subjects and including a wide range of sleep/wake schedules and caffeine doses. We then developed and validated an automated method to customize the UMP to an individual’s sleep-loss phenotype based on the individual’s PVT measurements. Finally, we embedded these capabilities into a smartphone app (Android and iPhone) and a Web tool, which allow users to enter sleep/wake schedules and caffeine consumption (doses and times), and obtain individual-specific or group-average performance predictions. The UMP predicted group-average PVT performance across 26 different sleep/wake schedules (from partial to total sleep loss) and 6 different caffeine doses (ranging from repeated 200 mg doses to single 600 mg dose) with errors ranging from 6% to 36%. Accounting for the effects of caffeine in the model improved prediction accuracy by up to 70%. Individualized UMP models improved prediction accuracy by up to 50% compared to a group-average model. The Web tool is freely available at: <https://2b-alert-web.bhsai.org>, and the 2B-Alert App is expected to be available by summer of 2017. The 2B-Alert App and Web provide practical means for personal fatigue management and for optimizing work/rest schedules. Disclaimer: The opinions and assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting the views of the U.S. Army or of the U.S. Department of Defense. This abstract has been approved for public release with unlimited distribution.