A data-based reduced-order model for dynamic simulation and control of district-heating networks

This study concerns the development of a data-based compact model for the prediction of the fluid temperature evolution in district heating (DH) pipeline networks. This so-called “reduced-order model” (ROM) is obtained from reduction of the conservation law for energy for each pipe segment to a semi-analytical input–output relation between the pipe outlet temperature and the pipe inlet and ground temperatures that can be identified from training data. The ROM basically is valid for generic pipe configurations involving 3D unsteady heat transfer and 3D steady flow as long as heat-transfer mechanisms are linearly dependent on the temperature field. Moreover, the training data can be generated by physics-based computational “full-order” models (FOMs) yet also by (calibration) experiments or field measurements. Performance tests using computational training data for a single-pipe configuration demonstrate that the ROM (i) can be successfully identified and (ii) can accurately describe the response of the outlet temperature to arbitrary input profiles for inlet and ground temperatures. Application of the ROM to two case studies, i.e. fast simulation of a small DH network and design of a controller for user-defined temperature regulation of a DH system, demonstrate its predictive ability and efficiency also for realistic systems. Dedicated cost analyses further reveal that the ROM may significantly reduce the computational costs compared to FOMs by (up to) orders of magnitude for higher-dimensional pipe configurations. These findings advance the proposed ROM as a robust and efficient simulation tool for practical DH systems with a far greater predictive ability than existing compact models

Modelling of T1 dispersion effects on fluid polarization in oil flow

In this article we use numerical simulations to study the effect of T1 dispersion on fluid polarization buildup in oil flow to characterize the sensitivity of both a conventional NMR concept (ROI located inside the polarization magnet) and a Earth's field NMR concept (ROI outside and downstream of the polarization magnet) to T1 dispersion of flowing samples. As a polarization field in both concepts we use a 90 cm long Halbach magnet. The T1 dispersion behavior of the oils is based on a set of crude oils that span a viscosity range of 0.7 cP up to 2·104 cP and T1 relaxation measurements for Larmor frequencies between 10 kHz and 20 MHz. Numerical simulations based on solving the Bloch-Torrey equation for the longitudinal magnetization component show that fluid polarization levels in a ROI of a Earth's field NMR system concept are much more strongly affected by T1 dispersion than in the conventional NMR system concept. As a result, we may conclude that the Earth's field NMR system design is less robust for measuring flowing samples that show strong T1 dispersion behavior. In comparison, the conventional NMR system design is relatively insensitive to the effect of T1 dispersion, as T1 dispersion effects were found to form a relatively small correction to the magnetization buildup. The conventional NMR system design consequently is the preferred implementation of a NMR system that operates on fluids with strong T1 dispersion behavior. We show that in the presence of T1 dispersion s = vT1(0)/Lm* may be used as a governing parameter for fluid polarization buildup, where T1(0) is the T1 relaxation time in the center of the polarization magnet, and we show how an modified analytical uniform field model can be used to describe fluid polarization for a uniform flow velocity distribution in the presence of T1 dispersion with an accuracy within 1% for the samples and field distribution considered in this study at industrially relevant flow velocities

Optimal Planning of Future District Heating Systems—A Review

This article provides the state-of-the-art on the optimal planning and design of future district heating (DH) systems. The purpose is to provide practical information of first-step actions for countries with a low DH market share for heating and cooling supply. Previous research showed that for those countries, establishing a heat atlas with accurate geographical data is an essential prerequisite to promote the development of DH systems. In this review, essential techniques for building a high-quality heat atlas are elaborated. This includes a review of methodologies for district thermal energy demand prediction and the status of the integration of sustainable resources in DH systems. In the meanwhile, technical barriers for the implementation of various sustainable heat sources are identified. Furthermore, technologies for the optimal planning of DH systems are discussed. This includes the review of current approaches for the optimal planning of DH systems, discussions on various novel configurations which have been actively investigated recently, and common upgrading measures for existing DH systems

Reinforcing Mechanisms of Coir Fibers in Light-Weight Aggregate concrete

Due to the requirement for developing more sustainable constructions, natural fibers from agricultural wastes, such as coir fibers, have been increasingly used as an alternative in concrete composites. However, the influence of coir fibers on the hydration and shrinkage of cement-based materials is not clear. In addition, limited information about the reinforcing mechanisms of coir fibers in concrete can be found. The goal of this research is to investigate the effects of coir fibers on the hydration reaction, microstructure, shrinkages, and mechanical properties of cement-based light-weight aggregate concrete (LWAC). Treatments on coir fibers, namely Ca(OH)2 and nano-sil-ica impregnation, are applied to further improve LWAC. Results show that leachates from fibers acting as a delayed accelerator promote cement hydration, and entrained water by fibers facilitates cement hydration during the whole process. The drying shrinkage of LWAC is increased by adding fibers, while the autogenous shrinkage decreases. The strength and toughness of LWAC are en-hanced with fibers. Finally, three reinforcement mechanisms of coir fibers in cement composites are discussed

Relating relative humidity fluctuations to damage in oak panel paintings by a simple experiment

Panel paintings are essentially wooden boards painted on one side. Due to the vapor resistance of the paint layer, changing ambient conditions lead to exchange of moisture on only one surface. Subsequently, a non-uniform moisture content profile is formed across the thickness of the board. As a result, differential expansion causes the board to bend in case of no mechanical restriction, or it leads to a build-up of stresses inside the material if restrained. Experiments with oak boards sealed on one side and exposed to a change in the ambient relative humidity (RH) were performed. By scaling, the response of any board with different thickness can be predicted. Since the bending of the board can be described as a linear system behavior, the frequency response can be predicted based on the step response. In combination with critical strains for wood and gesso from the literature, this gives insight into allowable RH fluctuations in terms of frequency and amplitude for different board thicknesses

Homogeneous water nucleation in carbon dioxide–nitrogen mixtures: Experimental study on pressure and carrier gas effects

New homogeneous nucleation experiments are presented at 240 K for water in carrier gas mixtures of nitrogen with carbon dioxide molar fractions of 5%, 15%, and 25%. The pulse expansion wave tube is used to test three different pressure conditions, namely, 0.1, 1, and 2 MPa. In addition, a restricted series of nucleation experiments is presented for 25% carbon dioxide mixtures at temperatures of 234 and 236 K at 0.1 MPa. As pressure and carbon dioxide content are increased, the nucleation rate increases accordingly. This behavior is attributed to the reduction in the water surface tension by the adsorption of carrier gas molecules. The new data are compared with theoretical predictions based on the classical nucleation theory and on extrapolations of empirical surface tension data to the supercooled conditions at 240 K. The extrapolation is carried out on the basis of a theoretical adsorption/surface tension model, extended to multi-component mixtures. The theoretical model appears to strongly overestimate the pressure and composition dependence. At relatively low pressures of 0.1 MPa, a reduction in the nucleation rates is found due to an incomplete thermalization of colliding clusters and carrier gas molecules. The observed decrease in the nucleation rate is supported by the theoretical model of Barrett, generalized here for water in multi-component carrier gas mixtures. The temperature dependence of the nucleation rate at 0.1 MPa follows the scaling model proposed by Hale [J. Chem. Phys. 122, 204509 (2005)]

Performance analysis of a K2CO3-based thermochemical energy storage system using a honeycomb structured heat exchanger

The application of thermal energy storage using thermochemical heat storage materials is a promising approach to enhance solar energy utilization in the built environment. Potassium carbonate (K2CO3) is one of the potential candidate materials to efficiently store thermal energy due to its high heat storage capacity and cost-effectiveness. In the present study, a 3-dimensional numerical model is developed for the exothermic hydration reaction of K2CO3. The heat produced from the reaction is transferred indirectly from the thermochemical material (TCM) bed through the walls of the honeycomb heat exchanger to a Heat Transfer Fluid (HTF). A parametric study is conducted for varying geometrical parameters of the honeycomb heat exchanger. The obtained results indicate that the reaction rate and heat transport in the TCM bed strongly depends on the geometrical parameters of the heat exchanger. Reducing the cell size of the honeycomb heat exchanger up to a certain level provides better thermal transport as well as improved reaction rate of the TCM bed. The results of this study provide detailed insight into the heat release processes occurring in a fixed bed of K2CO3. The study is useful for designing and optimizing thermo-chemical energy storage modules for the built environment

A dimensionally-reduced fracture flow model for poroelastic media with fluid entry resistance and fluid slip

We develop a model which couples the flow in a discrete fracture to a deformable porous medium. To account for the discrete representation of the fracture, a dimensionally-reduced fluid flow model is proposed. The fluid flow model incorporates both a reduced permeability of the fracture walls due to the skin effect, and a slip of fluid flowing along the permeable fracture walls. Biot's model for poroelastic media is coupled to a fracture flow model based on a thin-film approximation of the compressible Navier-Stokes equations. The fracture flow model incorporates a fluid entry resistance parameter to relate the leak-off through the fracture walls to a pressure jump across the fracture walls, and the Beavers-Joseph-Saffman slip rate coefficient to represent the fluid slip along the fracture walls. The numerical model is based on a thermodynamic framework in which all energy storage and dissipative mechanisms in the problem are identified, including the mechanisms related to the interface effects. The thermodynamic framework is employed to solve the nonlinear coupled problem up to a specified energy range through a Picard iteration technique and to study the model and its results. Studies are presented for a range of fluid entry resistance parameters and Beavers-Joseph-Saffman slip rate coefficients, showing the capability of the model to simulate skin and slip effects in a dimensionally-reduced fracture setting

Exploring the Electronic Structure of New Doped Salt Hydrates, Mg1–xCaxCl2·nH2O, for Thermochemical Energy Storage

Chloride-based salt hydrates, MgCl2·nH2O and CaCl2·nH2O (n = 0,1,2,4,6), are promising materials for thermochemical heat storage systems due to their high sorption energy capacity. However, both salts have their own shortcoming characteristics within the operational temperature of the thermochemical heat storage applications. While the higher hydrates of CaCl2·nH2O (n = 4,6) have a low melting point, the lower hydrates of MgCl2·nH2O (n = 0,1,2) can form the highly toxic and corrosive HCl gas. Both shortcomings cap the individual use of these salts to a restricted range of the available hydrates. A combination of these two salts showed to have the potential to overcome these shortcomings. The present study focuses on finding stable configurations of potential superior salt hydrate combinations using the evolutionary algorithm USPEX as well as manual mutations of known pristine structures. The newly found structures are less stable than the pure salts, but stable enough to be combined. Extensive electronic density-derived tools, like the Density Derived Electronic and Chemical (DDEC6) bond orders and net atomic charges, as well as Bader topological analysis, are used to predict the HCl gas formation based on the chemical environment in the new metastable structures. We find that doping MgCl2·nH2O with calcium considerably reduces HCl formation compared to its pure form, caused by a combination of the stronger Ca-Cl interaction than Mg-Cl and a less polar H2O molecule in a calcium environment than in a magnesium environment. This provides the possibility to shift the p, T-equilibrium curve of HCl outside the thermal storage operational window

Development of a scattering model for diatomic gas-solid surface interactions by an unsupervised machine learning approach

This work proposes a new stochastic gas-solid scattering model for diatomic gas molecules constructed based on the collisional data obtained from Molecular Dynamics (MD) simulations. The Gaussian Mixture (GM) approach, which is an unsupervised machine learning approach, is applied to H2 and N2 gases interacting with Ni surfaces in a two parallel walls system under rarefied conditions. The main advantage of this approach is that the entire translational and rotational velocity components of the gas molecules before and after colliding with the surface can be utilized for training the GM model. This creates the possibility to study also highly nonequilibrium systems, and accurately capture the energy exchange between the different molecular modes that cannot be captured by the classical scattering kernels. Considering the MD results as the reference solutions, the performance of the GM-driven scattering model is assessed in comparison with the Cercignani-Lampis-Lord (CLL) scattering model in different benchmarking systems: the Fourier thermal problem, the Couette flow problem, and a combined Fourier-Couette flow problem. This assessment is performed in terms of the distribution of the velocity components and energy modes, as well as accommodation coefficients. It is shown that the predicted results by the GM model are in better agreement with the original MD data. Especially, for H2 gas the GM model outperforms the CLL model. The results for N2 molecules are relatively less affected by changing the thermal and flow properties of the system which is caused by the presence of a stronger adsorption layer