Start-up Data Research Articles

Identification of Nitrification Kinetics for Activated Sludge Treating Leachate Using Combined Plant Start-up Data and Batch Kinetic Test

Identification of Nitrification Kinetics for Activated Sludge Treating Leachate Using Combined Plant Start-up Data and Batch Kinetic Test

Startup experiment with the newly installed lower tungsten divertor of KSTAR

Startup experiment with the newly installed lower tungsten divertor of KSTAR

Data-Driven Entrepreneurship in Green Hydrogen Economy: An Integrated Framework for Entrepreneurial Enterprises in the Era of Big Data

In the era of big data, in order to improve the aggregation effect of start-ups, a digital framework with a promoting role has been formed. This paper proposes a data-driven approach in the context of the green hydrogen economy. Firstly, the data function was used to collect, classify and sort out the entrepreneurial data to form an orderly data set. Then, with the help of data-driven functions, the nonlinear reorganization of start-ups is carried out to verify their discreteness, the correlation between the hydrogen economy and start-up data is mined, and an integrated framework is formed through iterative calculation. The results show that there is a significant correlation between the hydrogen economy and start-ups, and big data can drive the integrated development of start-ups, and the data-driven method proposed in this paper can accurately identify start-up data, with a recognition rate of 90%, which is better than the previous machine learning methods and decision tree methods, and has strong big data mining capabilities. Therefore, there is a significant correlation between the hydrogen economy, big data, and start-ups, and a data-driven approach can identify the relationship between the two and facilitate the construction of an integrated framework.

Rotor fault characterization study by considering normalization analysis, feature extraction, and a multi-class classifier

Background. Rotor faults are the most common malfunctions encountered, especially during the manufacturing stage, in asynchronous motors. These faults cause vibration in the motor torque and a decrease in efficiency. In recent years, the detection of rotor faults has been done using motor current. The reflection of rotor faults on motor current depends on slip, and therefore, the effect increases as the current grows. Good results are achieved in fault detection at nominal loads. However, especially when motor manufacturers are considered, testing the motor by loading it requires expensive testing equipment and long-term test procedures. Therefore, the detection of faults in the motor at no load is emphasized. However, since the effect of the fault decreases when the motor is at no load, fault detection becomes difficult. Generally, small-level faults cannot be detected. Objective. This study focuses on fault detection from the motor current at no load. The development current at no load was used to eliminate the negative effects of slip. However, since the slip is not constant, the change in frequency and amplitude values to be used as a feature makes the diagnosis difficult. Method. In this study, the spectrogram was used to evaluate the change during the start-up time. Thus, a standard dataset was determined for comparison. The texture properties of the spectrogram image were extracted using various methods. The extracted features were subjected to normalization analysis and classified using the k-NN algorithm. Results. In the classification phase, a classification accuracy of 98.66% was achieved using the k-NN method, and it was seen that the proposed method could be used for the detection of rotor faults. Conclusions. The study has successfully demonstrated that broken rotor bar faults in asynchronous motors can be diagnosed using the motor start-up data.

Efficiency Analysis of the Third Unit in Al-Khoums Steam Power Plant, Libya

The thermal and overall efficiency of the third unit in the Al-Khoums steam power plant were investigated in this paper. Two samples of data have been used: the first was collected from the start-up data sheet of the power plant with a load of 120 MWH, and the second was collected in June 2023 with a load of 96 MWH. This study reveals that the thermal efficiency of the unit decreased by 9.4% (from 40.4% to 36.6%) due to the life of the plant and the stoppage of extraction lines, and the overall efficiency decreased by 8.7% (from 36.7% to 33.5%). Moreover, heat rejected by the condenser increased in the second sample by 44 kJ/kg. Steam cycles for both study samples were presented by T-S diagrams using Engineering Equation Solver software (EES), and it was clear from those diagrams that the efficiency of the high-pressure turbine in the first sample is higher than the second one.

On the startup behavior of wormlike micellar networks: The effect of different salts bound to the same surfactant molecule

We report on shear startup data for two wormlike micellar solutions, differing only in concentration and type of two binding aromatic sodium salts. The surfactant molecule is cetylpiridinium chloride at a fixed concentration (100 mM). Sodium salicylate (NaSal) and diclofenac sodium (Diclo) are used as binding salts at concentrations 68 mM NaSal and 52 mM Diclo such that both systems are fully entangled and their linear viscoelastic response is essentially identical. Both systems show the linear response typical of a wormlike micellar solution, with terminal behavior at low frequencies, a well-defined moduli crossover, and a plateau modulus. In the nonlinear regime, however, the behavior of the two systems is totally different, suggesting that the molecular structure difference of the salts and their binding activity to the surfactant molecule are both crucial to determine the fast flow behavior. The NaSal solution shows a very complex rheological response, with strain hardening and very sharp stress peaks, whereas the solution containing Diclo behaves much like ordinary linear polymers, exhibiting pronounced overshoots as well as moderate undershoots in the transient shear viscosity, before approaching the steady state. This polymerlike behavior has also been proved by successfully comparing data with predictions of a constitutive equation recently adopted for both entangled polymers and linear wormlike micelles. As far as NaSal is concerned, a phenomenological model based on rubber network theory is developed, which describes the flow singularities. A physical interpretation of the different behavior in the nonlinear regime is also suggested.

Modeling and simulation of a multistage heat recovery steam generator

As the share of renewable energy increases in modern power grids, their inherent intermittency compels existing thermal power plants to become more agile and flexible in their operation. To achieve such flexibility, understanding the transient behavior of thermal power plants is key. In this regard, physics-based dynamic models are useful tools. They help in predicting performance and in exploring various operating conditions in a risk-free, cost-effective manner. To this end, this paper presents a multi-stage Heat Recovery Steam Generator (HRSG) model. Fast simulations are demonstrated for this three pressure-stage system with interconnected thermodynamic and mass transfer phenomena. The HRSG’s multi-physics behavior is captured through mathematically modeled and numerically simulated phase change, fluid dynamics, and thermal coupling. Heat exchange elements such as economizers and superheaters are modeled by directly solving the Unsteady Flow Energy Equation (UFEE). The phase change dynamics of the boiler are modeled using a multi-mode switching mechanism, where each mode is characterized by boiling/evaporation/condensation and heating/cooling phenomena. A judicious combination of spatially discretized or lumped and dynamic or quasi-static models is used to achieve reasonably accurate transient response while lowering the computational burden. In collaboration with Siemens Energy Inc., steady-state prediction capability and transient pressure behavior are validated with plant startup data from an operational HRSG.

Does intermittent supply result in hydraulic transients? Mixed evidence from two systems

Abstract Pressure transients can cause severe damage in continuous water supply pipe networks, but little is known about pressure transients in intermittent networks. Published examples of high-frequency pressure monitoring in intermittent networks are lacking. Intermittent supply can be caused by poor network condition and is associated with delivering less water, less frequently, and with poorer quality than continuous supply. Given the frequency with which intermittent systems drain, fill, and change supply regimes, pressure transients have been hypothesized to be common and to be one mechanism by which intermittent supply further degrades network condition. We present supply start-up data from two very different intermittent systems: a low-pressure, intermittent network in Delhi, India, and a higher-pressure intermittent network in Arraiján, Panama. Across monitoring locations at both sites, we did not detect substantial pressure transients due to pipe filling. In Arraiján, pump start-ups, pump shutdowns, and pipe bursts were associated with potentially problematic transients. We conclude that pipe filling in intermittent supply does not always result in concerning pressure transients. The largest risks to pipe conditions we observed were due to pumping changes in close succession; hence, we recommend that utilities operating intermittent (and continuous) systems leave adequate dissipation time between changes in pump operation.

Start-up considerations for a small vertical-axis wind turbine for direct wind-to-heat applications

Renewable production of space and water heating is needed for a sustainable society. The rotating shaft of a vertical-axis wind turbine can be equipped with a paddle wheel-style mixing impeller to directly heat a fluid by agitating or stirring the fluid. A Darrieus vertical-axis wind turbine, operating at or near its nameplate power capacity, is able to perform this function reliably as it is producing significant amounts of power; however, an autonomous wind-to-thermal system presents a challenge due to the difficulties associated with the start-up process of this type of turbine. The start-up difficulty is quantified herein by using a set of well-referenced vertical-axis wind turbine start-up data to derive the turbine’s torque and power values for each rotational velocity data point. It is shown that the turbine produces minimal positive torque during an extended region of operation around tip-speed ratio λ=1. A fluid-agitation thermal generator is considered by employing fluid mixing theory to compute the torque of a conceptual mixing impeller for different impeller diameters and styles. A thermal generator impeller is sized based on the derived experimental values and operational characteristics of the vertical-axis wind turbine data set. Thermodynamic analysis for the conceptual fluid-agitation generator shows that for an enclosed fluid volume = 1L, a fluid temperature rise of approximately ΔT=5°C can be achieved during one hour of system operation. The results demonstrate the potential of H-Darrieus turbines as renewable heat generating devices, while highlighting the need for careful system design to achieve successful start-up.

Analisis Perbandingan Algoritma Decision Tree, kNN, dan Naive Bayes untuk Prediksi Kesuksesan Start-up

Start-ups have a very important role in economic growth, the existence of a start-up can open up many new jobs. However, not all start-ups that are developing can become successful start-ups. This is because start-ups have a high failure rate, data shows that 75% of start-ups fail in their development. Therefore, it is important to classify the successful and failed start-ups, so that later it can be used to see the factors that most influence start-up success, and can also predict the success of a start-up. Among the many classifications in data mining, the Decision Tree, kNN, and Naïve Bayes algorithms are the algorithms that the authors chose to classify the 923 start-up data records that were previously obtained. The test results using cross-validation and T-test show that the Decision Tree Algorithm is the most appropriate algorithm for classifying in this case study. This is evidenced by the accuracy value obtained from the Decision Tree algorithm, which is greater than other algorithms, which is 79.29%, while the kNN algorithm has an accuracy value of 66.69%, and Naive Bayes is 64.21%.

НЕЙРО-НЕЧІТКА МОДЕЛЬ ІНФОРМАЦІЙНОЇ ТЕХНОЛОГІЇ КОМПЛЕКСНОЇ ОЦІНКИ РІВНЯ УСПІШНОСТІ STARTUP-ПРОЄКТІВ

Nowadays, there are sad statistics that about 90% of all startups have failed. That is why the development of methods and models for predicting the success of startup projects is significant.There is no research on using neuro-fuzzy systems for astartup success integrated assessment. This statement only em-phasizes the need to develop and implement such a system due to its undeniable relevance.Fuzzy systems are widespread in modern startup success forecasting models, but they have disadvantages like finding membership functions, the need for an expert to determine the rules and total adherence to the existing system rules. That iswhy the search for the possibilities to combine neural networks and fuzzy logic has become quite popular.Most of theexisting analysis and projects evaluation models use accurate data-based training, but it is not always possible to provide accurate startup data. The purpose of this research is to support decision-making in the creation of startup projects through the development of an automated information system for a comprehensive assessment of the startup success.A neuro-fuzzy information technology model for startup success level integrated assessment has been developed, consist-ing of 3 main subsystems. The data processing subsystem,subsystem of neuro-fuzzy assessment for projects, subsystem for searching for successful startup projects and selecting strategies for further startup development. The complex information system will allow you to get a success assessment, an individually formed strategy for project development, and use the experience of similar startups in the development.

Success Factors of Startups in the EU—A Comparative Study

The paper focuses on key success factors of startups in the European Union. Startup companies have a massive potential to boost the level of innovation and competitiveness of national economies. They are also uniquely equipped to provide extremely effective and flexible ways of meeting both existing and emerging market needs. However, the development of these microventures differs from country to country. Hence, we put forth a hypothesis that strategic success factors in the development of startups vary in highly developed and catching-up countries. Our main goal was to determine the key success factors of startups in the EU, and to classify the gap between developed and lagging Member States. For this purpose, we applied the method of component analysis on startup data available for selected the EU states. We managed to isolate 5 components explaining 72% of data variability, all of which can be linked to human capital as well as to formal and informal economic institutions. The results confirmed the validity of our hypothesis. We established that more developed countries offer an institutional competitive advantage to startups, while the gap in success factors between highly developed and catching-up countries can be attributed to human capital and to institutions. Based on our findings, we offer suggestions how to reduce this gap by improving formal and informal institutions via innovative public policy and by supporting education.

Experimental and theoretical investigations of the lateral vibrations of an unbalanced Jeffcott rotor

The current work experimentally explores and then theoretically examines the lateral vibrations of an unbalanced Jeffcott rotor-system working at several unbalance conditions. To this end, three conditions of eccentric masses are considered by using a Bently Nevada RK-4 rotor kit. Measurements of the steady-state as well as the startup data at rigid and flexible rotor states are captured by conducting a setup that mimics the vibration monitoring industrial practices. The linear governing equation of the considered rotor is extracted by adopting the Lagrange method on the basis of rigid rotor assumptions to theoretically predict the lateral vibrations. The dynamic features of the rotor system such as the linearized bearing induced stiffness are exclusively acquired from startup data. It is demonstrated that, with an error of less than 5%, the proposed two-degrees-of-freedom model can predict the flexural vibrations at rigid condition. While at flexible condition, it fails to accurately predict the dynamic response. In contrast to the other works where nonlinear mathematical models with some complexities are proposed to mathematically model the real systems, the present study illustrates the applicability of employing simple models to predict the dynamic response of a real rotor-system with an acceptable accuracy.

Linear wormlike micelles behave similarly to entangled linear polymers in fast shear flows

We report shear startup data on solutions of entangled linear wormlike micelles, only differing in the concentration of a binding aromatic salt. Wormlike micelles behave similarly to ordinary polymers in fast shear flows, exhibiting pronounced overshoots as well as tiny undershoots in transient shear viscosity, before approaching the steady state. The analogy is here emphasized by successfully comparing data with predictions of a constitutive equation recently adopted for ordinary entangled polymers. In the fast shear flow, entangled linear wormlike micelles appear to align, stretch, and tumble just like polymeric chains.

Shelf-life analysis of solid rocket engine using HTPB/AP based on kinetic-chemical parameters of DSC analysis and burn on a test bench

Propellants based on HTPB/AP (hydroxyl-terminated polybutadiene/ammonium perchlorate) are the most commonly used in most of the rocket engines used by the Brazilian Armed Forces. This work aimed at the possibility of extending its useful life (currently in 10 years) by performing chemical kinetic analysis of the energetic material via differential scanning calorimetry (DSC) and also performing computer simulation of aging process using the software Large-scale Atomic/Molecular Massively Parallel Simulator. The simulations presented the experimental behavior of the aging process, showing the bending and cross-link of the binder with the volume contraction and the energetic stabilization. Thermal analysis via DSC was performed in triplicate and in 3 heating ratios (5 °C, 10 °C and 15 °C) of rocket motor with 11-year shelf-life, using the Arrhenius equation to obtain its activation energy, using Ozawa and Kissinger kinetic methods, allowing comparison with manufacturing period data (standard motor). The obtained activation energies were 126.67 kJ/mol (Ozawa) and 122.85 kJ/mol (Kissinger), much higher than that of the aged propellants (~ 78 kJ/mol, based on literature data), showing that the propellant has not yet aged significantly. In addition, the kinetic parameters of internal pressure of the combustion chamber in 8 rocket engines with 11 years of shelf-life were also acquired, for comparison purposes with the engine start-up data.

How does urban agglomeration integration promote entrepreneurship in China? Evidence from regional human capital spillovers and market integration

Using firm birth records and startup data matched with cities' characteristics, this paper analyzes nearly 300 prefecture-level cities to examine the role of human capital and market access in shaping the economic geography of innovation-driven entrepreneurship in China. We document strong positive entrepreneurial effects of local human capital resources and market size as well as market integration and human capital spillovers from mega-urban agglomerations of integrated cities. Our estimates point to an elasticity of innovation-driven entrepreneurship with respect to human capital spillovers of 0.50–0.79. The elasticity with respect to market integration is 0.53–0.89. Our results also suggest heterogeneous human capital spillover and market integration effects across urban agglomerations. These effects are more robust in first-tier urban agglomerations because first-tier urban agglomerations have a stronger economic base and greater connectivity. Strong human capital spillover and large gains from access to surrounding economic mass jointly highlight the integrated development of mega-urban agglomerations in China. We discuss policy implications that concern promotion of local innovation-driven entrepreneurship by strengthening intercity coordination, building transportation and social infrastructure, and improving urban management.

Start-up timing behavior of single-loop oscillating heat pipes based on the second-order dynamic model

Abstract Oscillating heat pipes have the potential to combine with the grinding wheel to enhance heat transfer in grinding process to avoid thermal damage of workpiece and grinding wheel. Since the time of grinding process is short, it raises a requirement for a good start-up behavior of oscillating heat pipes inside grinding wheel. In order to understand the start-up behavior, a new method is proposed based on the second-order dynamic theory to represent and evaluate start-up process. Several parameters (i.e., rising and settling time, percent-overshoot) are defined to value quantitatively the start-up process. Accordingly, three start-up modes are discovered with respect to the evaporator temperature, which are over-damped, under-damped and transient start-up modes. The start-up behavior is discussed with both pure fluids and nanofluids. Results show that as the heating power increases, the start-up speed enhances, and over-damped start-up mode develops to under-damped or transition start-up mode. The start-up speed of DI water is faster at low heating power, while acetone and nano-diamond solution without dispersant show faster start-up speed at high heating power. This methodology will help to compare the start-up timing of the OHP experiments in literatures, providing a more robust way to analyze start-up data.

Modeling Unentangled Polystyrene Melts in Fast Elongational Flows

Recent data of unentangled polystyrene melts in startup elongational flow and subsequent relaxation [Matsumiya, Y.; Watanabe, H.; Masubuchi, Y.; Huang, Q.; Hassager, O. Nonlinear Elongational Rheology of Unentangled Polystyrene and Poly(p-Tert-Butylstyrene) Melts. Macromolecules 2018, 51 (23), 9710−9729] are here compared to the predictions of Brownian simulations of Fraenkel chains endowed with a monomeric friction coefficient that decreases with increasing the order parameter of the Kuhn segments. The model compares favorably with all startup data if a time delay in reducing the monomeric friction coefficient is accounted for in the fastest flows, a feature already observed by Matsumiya et al. The same model also describes the relaxation data except for a minor discrepancy in the longest relaxation time, probably due to the imperfect monodispersity of the sample and/or to a minor influence of topological interactions, not strong enough to be called entanglements. A discrepancy is also observed at the be...

Controller design using quantitative feedback theory for thermal power plant process

Abstract This paper proposes a controller design that is robust to parameter variations occurring in a Thermal Power Plant Process. Real time cold startup data is collected from NLC Tamilnadu Power Limited (NTPL), Tuticorin unit, of 500 MW capacity. This data is used for modelling the coal flow rate, air flow rate and feed water flow rate loops which will be controlled to ultimately control the generated electric power. Quantitative Feedback Theory is a technique used for controller design, obtaining the parameters of the PD controller that promotes robustness in the specified performance even with variations in the plant parameters. For a particular frequency, the magnitude and phase of the open loop gain and phase curve are acquired and solving the resultant equations confers us the tuning parameters of the controller. From the simulation results, it can be highlighted that the controller performs fairly well.

How Does Urban Agglomeration Integration Promote Entrepreneurship in China? Evidence from Regional Human Capital Spillovers and Market Integration

Using firm birth records and startup data matched with cities’ characteristics, this paper analyzes nearly 300 prefecture-level cities to examine the role of human capital and market access in shaping the economic geography of innovation-driven entrepreneurship in China. We document strong positive entrepreneurial effects of local human capital resources and market size as well as market integration and human capital spillovers from mega urban agglomerations of integrated cities. Our estimates point to an elasticity of innovation-driven entrepreneurship with respect to human capital spillovers of 0.50-0.79. The elasticity with respect to market integration is 0.53-0.89. Our results also suggest heterogeneous human capital spillover and market integration effects across urban agglomerations. These effects are more robust in first-tier urban agglomerations because first-tier urban agglomerations have a stronger economic base and greater connectivity. Strong human capital spillover and large gains from access to surrounding economic mass jointly highlight the integrated development of megaurban agglomerations in China. We discuss policy implications that concern promotion of local innovation-driven entrepreneurship by strengthening intercity coordination, building transportation and social infrastructure, and improving urban management.