Numerical Model for the Analysis of Thermal Transients in District Heating Networks

As District Heating (DH) networks are experiencing an evolution towards the so-called 4th generation, there is a need to update the currently used models to take into account the ever-increasing complexity of this technology. Indeed, to further improve the reduction in energy consumption and carbon-dioxide emissions, a wide range of technologies and management strategies are being introduced within district heating, such as a large exploitation of Renewable Energy Sources (RES). As a consequence, thermal transients assume a major importance, posing the need to redefine the relevant physical parameters and to develop a model which accurately describes their behaviour. In this framework, this paper proposes a quantitative analysis of the influence of the pipe heat-capacity on the model. Moreover, an equivalent-model, which is able to take into account the two heat capacities of steel and water in just one equation, is proposed and compared with two commonly used approaches. One of the features of the proposed model is the suitability for application to large networks. To prove its capabilities, an application to the Turin district heating network, which is among the largest systems in Europe, is proposed. Results show significant improvements in terms of accuracy over computational time ratio.

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Coupling of Charge Regulation and Conformational Equilibria in Linear Weak Polyelectrolytes: Treatment of Long-Range Interactions via Effective Short-Ranged and pH-Dependent Interaction Parameters

Polymers ◽

10.3390/polym10080811 ◽

2018 ◽

Vol 10 (8) ◽

pp. 811 ◽

Cited By ~ 6

Author(s):

Pablo Blanco ◽

Sergio Madurga ◽

Francesc Mas ◽

Josep Garcés

Keyword(s):

Long Range ◽

Ph Dependence ◽

Effective Interaction ◽

Interaction Parameters ◽

Computational Time ◽

Physical Parameters ◽

Wide Range ◽

Conformational Equilibria ◽

Ph Dependent ◽

Weak Polyelectrolytes

The classical Rotational Isomeric State (RIS) model, originally proposed by Flory, has been used to rationalize a wide range of physicochemical properties of neutral polymers. However, many weak polyelectrolytes of interest are able to regulate their charge depending on the conformational state of the bonds. Recently, it has been shown that the RIS model can be coupled with the Site Binding (SB) model, for which the ionizable sites can adopt two states: protonated or deprotonated. The resulting combined scheme, the SBRIS model, allows for analyzing ionization and conformational equilibria on the same foot. In the present work, this approach is extended to include pH-dependent electrostatic Long-Range (LR) interactions, ubiquitous in weak polyelectrolytes at moderate and low ionic strengths. With this aim, the original LR interactions are taken into account by defining effective Short-Range (SR) and pH-dependent parameters, such as effective microscopic protonation constants and rotational bond energies. The new parameters are systematically calculated using variational methods. The machinery of statistical mechanics for SR interactions, including the powerful and fast transfer matrix methods, can then be applied. The resulting technique, which we will refer to as the Local Effective Interaction Parameters (LEIP) method, is illustrated with a minimal model of a flexible linear polyelectrolyte containing only one type of rotating bond. LEIP reproduces very well the pH dependence of the degree of protonation and bond probabilities obtained by semi-grand canonical Monte Carlo simulations, where LR interactions are explicitly taken into account. The reduction in the computational time in several orders of magnitude suggests that the LEIP technique could be useful in a range of areas involving linear weak polyelectrolytes, allowing direct fitting of the relevant physical parameters to the experimental quantities.

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Understanding Limited Use of Amplification in Infants and Children Who Are Hard of Hearing

Perspectives on Hearing and Hearing Disorders in Childhood ◽

10.1044/hhdc25.1.15 ◽

2015 ◽

Vol 25 (1) ◽

pp. 15-23 ◽

Cited By ~ 1

Author(s):

Ryan W. McCreery ◽

Elizabeth A. Walker ◽

Meredith Spratford

Keyword(s):

Hard Of Hearing ◽

Hearing Aid ◽

Management Strategies ◽

Infants And Children ◽

Future Research ◽

Research Needs ◽

Case Examples ◽

Hearing Aid Use ◽

Wide Range ◽

In Infants And Children

The effectiveness of amplification for infants and children can be mediated by how much the child uses the device. Existing research suggests that establishing hearing aid use can be challenging. A wide range of factors can influence hearing aid use in children, including the child's age, degree of hearing loss, and socioeconomic status. Audiological interventions, including using validated prescriptive approaches and verification, performing on-going training and orientation, and communicating with caregivers about hearing aid use can also increase hearing aid use by infants and children. Case examples are used to highlight the factors that influence hearing aid use. Potential management strategies and future research needs are also discussed.

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RELaTED Project: New Developments on Ultra-Low Temperature District Heating Networks

Proceedings ◽

10.3390/proceedings2020065008 ◽

2020 ◽

Vol 65 (1) ◽

pp. 25

Author(s):

Antonio Garrido Marijuan ◽

Roberto Garay ◽

Mikel Lumbreras ◽

Víctor Sánchez ◽

Olga Macias ◽

...

Keyword(s):

Low Temperature ◽

High Performance ◽

Waste Heat ◽

District Heating ◽

Hot Water ◽

Thermal Systems ◽

Heating Source ◽

Wide Range ◽

Thermal Sources ◽

Heating Networks

District heating networks deliver around 13% of the heating energy in the EU, being considered as a key element of the progressive decarbonization of Europe. The H2020 REnewable Low TEmperature District project (RELaTED) seeks to contribute to the energy decarbonization of these infrastructures through the development and demonstration of the following concepts: reduction in network temperature down to 50 °C, integration of renewable energies and waste heat sources with a novel substation concept, and improvement on building-integrated solar thermal systems. The coupling of renewable thermal sources with ultra-low temperature district heating (DH) allows for a bidirectional energy flow, using the DH as both thermal storage in periods of production surplus and a back-up heating source during consumption peaks. The ultra-low temperature enables the integration of a wide range of energy sources such as waste heat from industry. Furthermore, RELaTED also develops concepts concerning district heating-connected reversible heat pump systems that allow to reach adequate thermal levels for domestic hot water as well as the use of the network for district cooling with high performance. These developments will be demonstrated in four locations: Estonia, Serbia, Denmark, and Spain.

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MOSAIK and FMI-Based Co-Simulation Applied to Transient Stability Analysis of Grid-Forming Converter Modulated Wind Power Plants

Applied Sciences ◽

10.3390/app11052410 ◽

2021 ◽

Vol 11 (5) ◽

pp. 2410

Author(s):

Nakisa Farrokhseresht ◽

Arjen A. van der Meer ◽

José Rueda Torres ◽

Mart A. M. M. van der Meijden

Keyword(s):

Power System ◽

Time Domain ◽

Power Plants ◽

Transient Stability ◽

Renewable Energy Sources ◽

Critical Factor ◽

Primary Control ◽

Simulation Approach ◽

Wide Range ◽

Grid Side

The grid integration of renewable energy sources interfaced through power electronic converters is undergoing a significant acceleration to meet environmental and political targets. The rapid deployment of converters brings new challenges in ensuring robustness, transient stability, among others. In order to enhance transient stability, transmission system operators established network grid code requirements for converter-based generators to support the primary control task during faults. A critical factor in terms of implementing grid codes is the control strategy of the grid-side converters. Grid-forming converters are a promising solution which could perform properly in a weak-grid condition as well as in an islanded operation. In order to ensure grid code compliance, a wide range of transient stability studies is required. Time-domain simulations are common practice for that purpose. However, performing traditional monolithic time domain simulations (single solver, single domain) on a converter-dominated power system is a very complex and computationally intensive task. In this paper, a co-simulation approach using the mosaik framework is applied on a power system with grid-forming converters. A validation workflow is proposed to verify the co-simulation framework. The results of comprehensive simulation studies show a proof of concept for the applicability of this co-simulation approach to evaluate the transient stability of a dominant grid-forming converter-based power system.

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Trends in Molecular Diagnosis and Diversity Studies for Phytosanitary Regulated Xanthomonas

Microorganisms ◽

10.3390/microorganisms9040862 ◽

2021 ◽

Vol 9 (4) ◽

pp. 862

Author(s):

Vittoria Catara ◽

Jaime Cubero ◽

Joël F. Pothier ◽

Eran Bosis ◽

Claude Bragard ◽

...

Keyword(s):

Molecular Diagnosis ◽

Bacterial Species ◽

Management Strategies ◽

Diagnostic Methods ◽

Plant Diseases ◽

Wild Plants ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Wide Range ◽

Diversity Studies

Bacteria in the genus Xanthomonas infect a wide range of crops and wild plants, with most species responsible for plant diseases that have a global economic and environmental impact on the seed, plant, and food trade. Infections by Xanthomonas spp. cause a wide variety of non-specific symptoms, making their identification difficult. The coexistence of phylogenetically close strains, but drastically different in their phenotype, poses an added challenge to diagnosis. Data on future climate change scenarios predict an increase in the severity of epidemics and a geographical expansion of pathogens, increasing pressure on plant health services. In this context, the effectiveness of integrated disease management strategies strongly depends on the availability of rapid, sensitive, and specific diagnostic methods. The accumulation of genomic information in recent years has facilitated the identification of new DNA markers, a cornerstone for the development of more sensitive and specific methods. Nevertheless, the challenges that the taxonomic complexity of this genus represents in terms of diagnosis together with the fact that within the same bacterial species, groups of strains may interact with distinct host species demonstrate that there is still a long way to go. In this review, we describe and discuss the current molecular-based methods for the diagnosis and detection of regulated Xanthomonas, taxonomic and diversity studies in Xanthomonas and genomic approaches for molecular diagnosis.

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A column-and-constraint generation algorithm for two-stage stochastic programming problems

Top ◽

10.1007/s11750-021-00593-2 ◽

2021 ◽

Author(s):

Denise D. Tönissen ◽

Joachim J. Arts ◽

Zuo-Jun Max Shen

Keyword(s):

Stochastic Programming ◽

Benders Decomposition ◽

Equivalent Model ◽

Computational Time ◽

Two Stage ◽

Generation Algorithm ◽

Constraint Generation ◽

Deterministic Equivalent ◽

Location Routing ◽

Relative Tolerance

AbstractThis paper presents a column-and-constraint generation algorithm for two-stage stochastic programming problems. A distinctive feature of the algorithm is that it does not assume fixed recourse and as a consequence the values and dimensions of the recourse matrix can be uncertain. The proposed algorithm contains multi-cut (partial) Benders decomposition and the deterministic equivalent model as special cases and can be used to trade-off computational speed and memory requirements. The algorithm outperforms multi-cut (partial) Benders decomposition in computational time and the deterministic equivalent model in memory requirements for a maintenance location routing problem. In addition, for instances with a large number of scenarios, the algorithm outperforms the deterministic equivalent model in both computational time and memory requirements. Furthermore, we present an adaptive relative tolerance for instances for which the solution time of the master problem is the bottleneck and the slave problems can be solved relatively efficiently. The adaptive relative tolerance is large in early iterations and converges to zero for the final iteration(s) of the algorithm. The combination of this relative adaptive tolerance with the proposed algorithm decreases the computational time of our instances even further.

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A Computational Study on the Role of Parameters for Identification of Thyroid Nodules by Infrared Images (and Comparison with Real Data)

Sensors ◽

10.3390/s21134459 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4459

Author(s):

José R. González ◽

Charbel Damião ◽

Maira Moran ◽

Cristina A. Pantaleão ◽

Rubens A. Cruz ◽

...

Keyword(s):

Heat Transfer ◽

Thyroid Nodules ◽

Numerical Study ◽

Computational Study ◽

Internal Heat ◽

Heat Transfer Process ◽

The Body ◽

Physical Parameters ◽

Infrared Sensors ◽

Wide Range

According to experts and medical literature, healthy thyroids and thyroids containing benign nodules tend to be less inflamed and less active than those with malignant nodules. It seems to be a consensus that malignant nodules have more blood veins and more blood circulation. This may be related to the maintenance of the nodule’s heat at a higher level compared with neighboring tissues. If the internal heat modifies the skin radiation, then it could be detected by infrared sensors. The goal of this work is the investigation of the factors that allow this detection, and the possible relation with any pattern referent to nodule malignancy. We aim to consider a wide range of factors, so a great number of numerical simulations of the heat transfer in the region under analysis, based on the Finite Element method, are performed to study the influence of each nodule and patient characteristics on the infrared sensor acquisition. To do so, the protocol for infrared thyroid examination used in our university’s hospital is simulated in the numerical study. This protocol presents two phases. In the first one, the body under observation is in steady state. In the second one, it is submitted to thermal stress (transient state). Both are simulated in order to verify if it is possible (by infrared sensors) to identify different behavior referent to malignant nodules. Moreover, when the simulation indicates possible important aspects, patients with and without similar characteristics are examined to confirm such influences. The results show that the tissues between skin and thyroid, as well as the nodule size, have an influence on superficial temperatures. Other thermal parameters of thyroid nodules show little influence on surface infrared emissions, for instance, those related to the vascularization of the nodule. All details of the physical parameters used in the simulations, characteristics of the real nodules and thermal examinations are publicly available, allowing these simulations to be compared with other types of heat transfer solutions and infrared examination protocols. Among the main contributions of this work, we highlight the simulation of the possible range of parameters, and definition of the simulation approach for mapping the used infrared protocol, promoting the investigation of a possible relation between the heat transfer process and the data obtained by infrared acquisitions.

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Improved Modeling of a Multi-Level Inverter for TACS to Reduce Computational Time and Improve Accuracy

Energies ◽

10.3390/en14040849 ◽

2021 ◽

Vol 14 (4) ◽

pp. 849

Author(s):

Sung-An Kim

Keyword(s):

Mechanical Model ◽

Simulation Software ◽

Computational Time ◽

Electrical Model ◽

Conventional Model ◽

Switching Operation ◽

Air Compressor ◽

Power Semiconductors ◽

Proposed Model ◽

Multi Level

A modeling of a turbo air compressor system (TACS), with a multi-level inverter for driving variable speed, combining an electrical model of an electric motor drive system (EMDS) and a mechanical model of a turbo air compressor, is essential to accurately analyze dynamics characteristics. Compared to the mechanical model, the electrical model has a short sampling time due to the high frequency switching operation of the numerous power semiconductors inside the multi-level inverter. This causes the problem of increased computational time for dynamic characteristics analysis of TACS. To solve this problem, the conventional model of the multi-level inverter has been proposed to simplify the switching operation of the power semiconductors, however it has low accuracy because it does not consider pulse width modulation (PWM) operation. Therefore, this paper proposes an improved modeling of the multi-level inverter for TACS to reduce computational time and improve the accuracy of electrical and mechanical responses. In order to verify the reduced computational time of the proposed model, the conventional model using the simplified model is compared and analyzed using an electronic circuit simulation software PSIM. Then, the improved accuracy of the proposed model is verified by comparison with the experimental results.

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Simulation Model to Analyze the Consequences of DC Faults in MMC-Based HVDC Stations

Electricity ◽

10.3390/electricity2020008 ◽

2021 ◽

Vol 2 (2) ◽

pp. 124-142

Author(s):

Davin Guedon ◽

Philippe Ladoux ◽

Sébastien Sanchez ◽

Sébastien Cornet

Keyword(s):

Power Transmission ◽

Renewable Energy Sources ◽

Energy Sources ◽

Modular Multilevel Converter ◽

Multilevel Converter ◽

Circuit Breakers ◽

High Voltage Direct Current ◽

Proposed Model ◽

Proper Design ◽

Reliability And Availability

The global development of high-voltage direct-current (HVDC) systems in fields such as renewable energy sources, interconnection of asynchronous grids or power transmission over great distances, is unquestionably important. Though widely used, the modular multilevel converter with half-bridge cells is sensitive to DC pole-to-pole faults and the time-response of the protections is critical. Reliability and availability are paramount: circuit-breakers must minimize the effects of any fault on the converter, while ensuring rapid restart. This paper focuses on the modelling aspects to analyse the behaviour of HVDC stations during DC pole-to-pole faults, using either AC or DC circuit-breakers, with different parameters. The proposed model can represent the main issues met by the converter cells during DC faults, such as semiconductor overcurrents and overvoltages, allowing a proper design of the cells.

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Prediction of Dead Oil Viscosity: Machine Learning vs. Classical Correlations

Energies ◽

10.3390/en14040930 ◽

2021 ◽

Vol 14 (4) ◽

pp. 930

Author(s):

Fahimeh Hadavimoghaddam ◽

Mehdi Ostadhassan ◽

Ehsan Heidaryan ◽

Mohammad Ali Sadri ◽

Inna Chapanova ◽

...

Keyword(s):

Machine Learning ◽

Viscosity Data ◽

Oil Viscosity ◽

Pvt Data ◽

Proposed Model ◽

Wide Range ◽

Engineering Problems ◽

Functional Forms ◽

Insight Into

Dead oil viscosity is a critical parameter to solve numerous reservoir engineering problems and one of the most unreliable properties to predict with classical black oil correlations. Determination of dead oil viscosity by experiments is expensive and time-consuming, which means developing an accurate and quick prediction model is required. This paper implements six machine learning models: random forest (RF), lightgbm, XGBoost, multilayer perceptron (MLP) neural network, stochastic real-valued (SRV) and SuperLearner to predict dead oil viscosity. More than 2000 pressure–volume–temperature (PVT) data were used for developing and testing these models. A huge range of viscosity data were used, from light intermediate to heavy oil. In this study, we give insight into the performance of different functional forms that have been used in the literature to formulate dead oil viscosity. The results show that the functional form f(γAPI,T), has the best performance, and additional correlating parameters might be unnecessary. Furthermore, SuperLearner outperformed other machine learning (ML) algorithms as well as common correlations that are based on the metric analysis. The SuperLearner model can potentially replace the empirical models for viscosity predictions on a wide range of viscosities (any oil type). Ultimately, the proposed model is capable of simulating the true physical trend of the dead oil viscosity with variations of oil API gravity, temperature and shear rate.

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