A solar cooling facility with two forms of energy storage, electrochemical (batteries) and thermal (tanks containing the heat transfer fluid, HTF), is simulated. The technical specifications used in the simulation are taken from a recently installed system in an institutional building at the University of Almería (Spain). Electricity generated by photovoltaic (PV) panels is either stored in a battery bank, or supplied directly to the chiller, which is also connected to the grid as a backup. The HTF circulates through a storage tank and is driven to a heat exchanger to cover the refrigeration demand. The whole system is modeled in TRNSYS with the corresponding meteorological data: the PV array has a peak power of 23.4 kW, the compression chiller power is 70 kWt, and the building demands of refrigeration from high and low season amount to 413.5 kWh/day and 62.8 kWh/day, respectively. The battery bank capacity is 40.8 kWh and the tank has a volume of 4000 L. Different configurations of energy storage (only electrical, only thermal, and hybrid) are tested for both demands. The results show that the refrigeration needs can be covered with solar energy and storage in the low season, with a surplus that can be driven to the building. In the high demand season, an extra input from the grid is needed as the current facility covers 89.3% of the total electricity requirements per day (54.5% if no storage is used). Finally, the system performance is evaluated over an intermediate-demand month. Overall, it is found that electrical consumption from the grid is minimal when batteries are used, either alone or in conjunction with thermal storage.

In this study, the effect of internal structuring in a thermal energy storage tank filled with phase change material (PCM) capsules on its performance was investigated. A laboratory-scale tank with a total capacity of 60 litres, connected to a pilot facility providing cold heat transfer fluid or a heat load, has been used. The system is intended to model space cooling, so the PCM was selected with a freezing point of-3 degrees C, and encapsulated with different geometries, which can be oriented vertically or horizontally and parallel or perpendicular to the flow. The amount of energy stored in the tank was calculated for all configurations. The highest energy storage and most effective energy recovery were observed with vertically oriented, disk-shaped capsules. The results also indicate that energy recovery from sensible heat is more efficient than from latent heat, although latent heat storage allows for greater overall energy accumulation and recovery. An important subcooling is also reported, as the inlet fluid must be cooled below-8 degrees C to freeze all the PCM in the storage tank, and reach the maximum load capacity (more than 500 kJ per kilogramme of PCM). Finally, the continuous operation of charging and discharging cycles was studied, showing that the energy in the tank varies between 80% and 30% of its total capacity in every cycle. The analysis also highlighted the significant impact of thermal gains and losses to or from the surrounding environment.

Dynamical heterogeneities are one of the hallmarks of supercooled liquids, and their properties and relevance have been studied with theory, simulations and experiments. In this work, we propose to monitor the dynamics of tracer particles (passive microrheology) to analyze the dynamical heterogeneities in a system of hard colloids close to the glass transition density, using Langevin dynamics simulations and mode coupling theory. Different observables, typical in the study of the dynamical heterogeneities are adapted to be calculated from the trajectory of a single tracer particle. The tracer dynamics shows a transition from a regime where it is most decoupled from the bath for small tracer size to a strong coupling regime for large tracers. Both theory and simulations show that the non-Gaussian parameter of the tracer is maximal for tracer sizes at the crossover between both regimes, and is highly dependent on the bath density. The dynamic susceptibility is also studied, but this parameter shows a minor dependence on both the tracer size or the bath density. Finally, the existence of regions with different mobility is also studied with microrheology. Although the tracer trajectory indeed shows stages with increased mobility, the estimated size of the regions decreases with the bath density, contrary to the results from cluster analysis in the bulk.

We investigate the diffusion of an intruder in a granular gas, with both components modeled as smooth hard spheres immersed in a low-viscosity carrier fluid to form a particle-laden suspension. In this system, dissipative particle collisions coexist with the action of a solvent. The latter is modeled via a viscous drag force and a stochastic Langevin-like force proportional to the background fluid temperature. Building on previous kinetic theory and random-walk results of the tracer diffusion coefficient [Phys. Rev. E 108, 024903 (2023)2470-004510.1103/PhysRevE.108.024903], where random-walk predictions were compared with Chapman-Enskog results up to the second Sonine approximation, we assess the robustness of the Enskog framework by incorporating molecular dynamics simulations, using direct simulation Monte Carlo results as an intermediate reference. In particular, we focus on the intruder velocity autocorrelation function, considering intruders' different masses (from 0.01 to 100 times the mass of the granular particles), and analyze the behavior of the intruder temperature and diffusion coefficient. Our results clarify the influence of the friction parameter and the conditions under which Enskog kinetic theory reliably describes intruder diffusion in granular suspensions.

The dynamics of the New York Stock Exchange during the past decade is studied using observables borrowed from the study of glass-forming liquids. Using the log-price as equivalent to the particle position, the density autocorrelation function is calculated, which shows a stretched exponential decay. The Kohlrausch law correctly describes the decay, and the dependencies of the stretching exponent and time-scale with the wavenumber follow the same trends as for supercooled liquids. The equivalent of the overlap correlation function is also calculated and analyzed. The dynamic heterogeneities are studied using the non-Gaussian parameter and the dynamic susceptibilities, calculated from both correlation functions. The dynamic susceptibility grows from zero at short times to describe a maximum in the same time scale as the decay of the corresponding correlation function, and decays back to zero for long times. Finally, we show that avalanches of all sizes are present in the system, mimicking critical behavior previously discussed in glasses.

Experiments and simulations have been used to study the freezing and melting kinetics of a single capsule containing a phase change material (PCM) for thermal energy storage. A commercial encapsulated PCM (EPCM) has been selected, with a melting/freezing temperature of approximately -3 degrees C, and the effect of the inclination angle on the phase change kinetics has been studied. Experimentally, the freezing and melting times have been determined using a thermocouple located in the center of the capsule. The results show a non-monotonic trend in the freezing time with the inclination angle, with a maximum at 45 degrees, degrees , both in the simulations and experiments. For the melting, a decreasing trend is observed in the simulations, which cannot be verified experimentally due to the measurement errors. Additionally, the simulations indicate that the misallocation of the internal probe within the nodule center can affect the results only marginally. Finally, the simulations show that the loose material within the capsule slows down the freezing, and increases the effect of the inclination angle.

Microrheology (MR) has emerged as a powerful tool for unraveling the intricate local viscoelastic properties of various soft materials. By tracking the free (passive MR) or forced (active MR) diffusion of a tracer, valuable insights into the mechanical characteristics of the host system can be obtained. In this study, we investigate the forced diffusion of a spherical tracer within isotropic and smectic liquid crystal phases of hard rod-like particles. Our findings reveal superdiffusive behaviour induced by external forces, particularly pronounced when these are aligned parallel to the nematic director. Analysis of the dynamical susceptibility unveils heterogeneities strongly correlated with the magnitude and orientation of applied forces, highlighting the system's critical dependence on structural ordering. Intriguingly, we observe that tracer superdiffusion, driven by external forces and evident across all relevant system directions, does not demonstrate a strong correlation with resulting dynamical heterogeneities.

One of the strategies to reduce the complexity of N -body simulations is the computation of the neighbour list. However, this list needs to be updated from time to time, with a high computational cost. This paper focuses on the use of quantum computing to accelerate such a computation. Our proposal is based on a well-known oracular quantum algorithm (Grover). We introduce an efficient quantum circuit to build the oracle that marks pairs of closed bodies, and we provide three novel algorithms to calculate the neighbour list under several hypotheses which take into account a-priori information of the system. We also describe a decision methodology for the actual use of the proposed quantum algorithms. The performance of the algorithms is tested with a statistical simulation of the oracle, where a fixed number of pairs of bodies are set as neighbours. A statistical analysis of the number of oracle queries is carried out. The results obtained with our simulations indicate that when the density of bodies is low, our algorithms clearly outperform the best classical algorithm in terms of oracle queries.

This work presents a theoretical analysis of the motion of a tracer colloid driven by a time-dependent force through a viscoelastic fluid. The recoil of the colloid after application of a strong force is determined. It provides insights into the elastic forces stored locally in the fluid and their weakening by plastic processes. We generalize the mode-coupling theory of microrheology to include time-dependent forces. After deriving the equations of motion for the tracer correlator and simplifying to a schematic model, we apply the theory to a switch-off force protocol that features the recoiling of the tracer after cessation of the driving. We also include Langevin dynamics simulations to compare to the results of the theory. A nonmonotonic trend of the recoil amplitude is found in the theory and confirmed in the simulations. The linear-response approximation is also verified in the small-force regime. While the overall agreement between simulation and theory is good, simulation shows that the theory predicts a too strong nonmonotonous dependence of the recoil distance on the applied force.

Quantum computing has emerged in recent years as an alternative to classical computing, which could improve the latter in solving some types of problems. One of the quantum programming models, Adiabatic Quantum Computing, has been successfully used to solve problems such as graph partitioning, traffic routing, and task scheduling. In this paper, the focus is on the scheduling of the problem of unrelated parallel machines, where the processing time of tasks on any of the available processing elements is known. Moreover, the proposed model is extended in two relevant aspects for this kind of problem: the existence of some degree of priority of tasks, and the introduction of a delay or penalty every time a processing unit or machine changes the type of task that executes.In all cases, the problem is expressed as Quadratic Unconstrained Binary Optimization, which can be subsequently solved using quantum annealers. The quantum nonlinear programming framework discussed in this work consists of three steps: quadratic approximation of cost function, a binary representation of parameter space, and solving the resulting Quadratic Unconstrained Binary Optimiza-tion on the quantum annealer platform D-Wave. One of the novelties in tackling this problem is the compaction of the model bearing in mind the repetitions of each task, to allow solving larger scheduling problems with the quantum resources available in the experimentation platform. An estimation of the number of qubits required in relation to the scheduling parameters is analyzed. The models have been implemented on the D-Wave platform and validated with respect to other traditional methods. Furthermore, the proposed extensions to consider priorities and to switch the delay of tasks have been analyzed using a case study.& COPY; 2023 Elsevier B.V. All rights reserved.

The dynamics of a tracer particle in a bath of quasi-hard colloidal spheres is studied by Langevin dynamics simulations and mode coupling theory (MCT); the tracer radius is varied from equal to up to seven times larger than the bath particles radius. In the simulations, two cases are considered: freely diffusing tracer (passive microrheology) and tracer pulled with a constant force (active microrheology). Both cases are connected by linear response theory for all tracer sizes. It links both the stationary and transient regimes of the pulled tracer (for low forces) with the equilibrium correlation functions; the velocity of the pulled tracer and its displacement are obtained from the velocity auto-correlation function and the mean squared displacement, respectively. The MCT calculations give insight into the physical mechanisms: At short times, the tracer rattles in its cage of neighbours, with the frequency increasing linearly with the tracer radius asymptotically. The long-time tracer diffusion coefficient from passive microrheology, which agrees with the inverse friction coefficient from the active case, arises from the transport of transverse momentum around the tracer. It can be described with the Brinkman equation for the transverse flow field obtained in extension of MCT, but cannot be recovered from the MCT kernel coupling to densities only. The dynamics of the bath particles is also studied; for the unforced tracer the dynamics is unaffected. When the tracer is pulled, the velocity field in the bath follows the prediction of the Brinkman model, but different from the case of a Newtonian fluid.

In this paper we propose a new measure of market efficiency based on the average response of a market price after a market event by using Linear Response Theory. It is shown that the average response to an event in different markets agrees fairly well with this theory’s prediction from equilibrium data in absence of external forces or events. In this work it is first found that Linear Response efficiently resolves price dynamics at moderately perturbed financial markets of different types. Namely we study Forex markets, the S&P500 index, Commodities markets and the Bitcoin-US dollar one. Furthermore, we determine a measure of market inefficiency, which can be used to compare the inefficiency between different assets and securities.

Quantum computing has emerged in recent years as an alternative to classical computing, which could improve the latter in solving some types of problems. One of the quantum programming models, Adiabatic Quantum Computing, has been successfully used to solve problems such as graph partitioning, traffic routing and task scheduling. Specifically, in this paper we focus on the scheduling on unrelated parallel machines problem. It is a workload-balancing problem where the processing time of any procedure executed on any of the available processing elements is known. Here, the problem is expressed as Quadratic Unconstrained Binary Optimisation, which can be subsequently solved using quantum annealers. The quantum nonlinear programming framework discussed in this work consists of three steps: quadratic approximation of cost function, binary representation of parameter space, and solving the resulting Quadratic Unconstrained Binary Optimisation. One of the novelties in tackling this problem has been to compact the model bearing in mind the repetitions of each task, to make it possible to solve larger scheduling problems.

The rheology of colloidal suspensions is of utmost importance in a wide variety of interdisciplinary applications in formulation technology, determining equally interesting questions in fundamental science. This is especially intriguing when colloids exhibit a degree of long-range positional or orientational ordering, as in liquid crystals (LCs) of elongated particles. Along with standard methods, microrheology (MR) has emerged in recent years as a tool to assess the mechanical properties of materials at the microscopic level. In particular, by active MR one can infer the viscoelastic response of a soft material from the dynamics of a tracer particle being dragged through it by external forces. Although considerable efforts have been made to study the diffusion of guest particles in LCs, little is known about the combined effect of tracer size and directionality of the dragging force on the system's viscoelastic response. By dynamic Monte Carlo simulations, we apply active MR to investigate the viscoelasticity of self-assembling smectic (Sm) LCs consisting of rodlike particles. In particular, we track the motion of a spherical tracer whose size is varied within a range of values matching the system's characteristic length scales and being dragged by constant forces that are parallel, perpendicular, or at 45° to the nematic director. Our results reveal a uniform value of the effective friction coefficient as probed by the tracer at small and large forces, whereas a nonlinear, force-thinning regime is observed at intermediate forces. However, at relatively weak forces the effective friction is strongly determined by correlations between the tracer size and the structure of the host fluid. Moreover, we also show that external forces forming an angle with the nematic director provide additional details that cannot be simply inferred from the mere analysis of parallel and perpendicular forces. Our results highlight the fundamental interplay between tracer size and force direction in assessing the MR of Sm LC fluids.

Current quantum computers have a limited number of resources and are heavily affected by internal and external noise. Therefore, small, noise-tolerant circuits are of great interest. With regard to circuit size, it is especially important to reduce the number of required qubits. Concerning to fault-tolerance, circuits entirely built with Clifford+T gates allow the use of error correction codes. However, the T-gate has an excessive cost, so circuits with a high number of T-gates should be avoided. This work focuses on optimising in such terms an operation that is widely used in larger circuits and algorithms: the calculation of the absolute-value of two’s complement encoded integers. The proposed circuit halves the number of required T gates with respect to the best circuit currently available in the literature. Moreover, our circuit requires at least 2 qubits less than the other circuits for such an operation.

Particle tracking in soft materials allows one to characterise the material's local viscoelastic response, a technique referred to as microrheology (MR). In particular, MR can be especially powerful to ponder the impact of structural ordering on the tracer's transport mechanism and thus disclose intriguing elements that cannot be observed in isotropic fluids. In this work, we perform Dynamic Monte Carlo simulations of isotropic and liquid-crystalline phases of rod-like particles and employ MR to characterise their linear viscoelastic response. By incorporating tracers of different diameters, we can assess the combined effect of size and ordering across the relevant time and length scales of the systems' relaxation. While the dynamics of small tracers is dramatically determined by the background ordering, sufficiently large trac-ers have a reduced perception of the medium nanostructure and this difference directly influences the observed MR. Our results agree very well with the picture of a microviscosity increasing with the relevant system length scales, but also suggest the crucial relevance of long-ranged order as a key element gov-erning the system's viscoelastic response.(c) 2022 Elsevier B.V. All rights reserved.

Understanding the rheology of colloidal suspensions is crucial in the formulation of a wide selection of industry-relevant products, such as paints, foods and inks. To characterise the viscoelastic behaviour of these soft materials, one can analyse the microscopic dynamics of colloidal tracers diffusing through the host fluid and generating local deformations and stresses. This technique, referred to as microrheology, links the bulk rheology of fluids to the microscopic dynamics at the particle scale. If tracers are subjected to external forces, rather than freely diffusing, it is called active microrheology. Motivated by the impact of microrheology in providing information on local structure in complex systems such as colloidal glasses, active matter or biological systems, we have extended the dynamic Monte Carlo (DMC) technique to investigate active microrheology in colloidal suspensions. The original DMC theoretical framework, able to accurately describe the Brownian dynamics of colloids at equilibrium, is here reconsidered and expanded to describe the effects of an external force pulling a tracer embedded in isotropic colloidal suspensions at different densities. To this end, we studied the dynamics of a spherical tracer dragged by a constant external force through a bath of spherical and rod-like particles of comparable size. We could extract valuable details on its effective friction coefficient, being constant at small and large values of the external force, but otherwise displaying a nonlinear behaviour that indicates the occurrence of a force-thinning regime. Our DMC simulation results are in excellent quantitative agreement with past Langevin dynamics simulations and theoretical works for the bath of spherical colloids. The bath of rod-like particles is studied in the isotropic phase, and displays an example where DMC is more convenient than Brownian or Langevin dynamics, in this case, in dealing with particle rotation.

The volatility and log-price collective movements among stocks of a given market are studied in this work using co-movement functions inspired by similar functions in the physics of many-body systems, where the collective motions are a signal of structural rearrangement. This methodology is aimed to identify the cause of coherent changes in volatility or price. The function is calculated using the product of the variations in volatility (or price) of a pair of stocks, averaged over all pair particles. In addition to the global volatility co-movement, its distribution according to the volatility of the stocks is also studied. We find that stocks with similar volatility tend to have a greater co-movement than stocks with dissimilar volatility, with a general decrease in co-movement with increasing volatility. On the other hand, when the average volatility (or log-price) is subtracted from the stock volatility (or log-price), the co-movement decreases notably and becomes almost zero. This result, interpreted within the background of many body physics, allows us to identify the index motion as the main source for the co-movement. Finally, we confirm that during crisis periods, the volatility and log-price co-movement are much higher than in calmer periods.

The performance of different thermal energy storing systems to provide over-night air-conditioning for a limited space in an institutional building in south Spain are compared with conventional air-conditioning (both for refrigeration and heating). In summer, the storage tanks are charged with a solar-assisted absorption chiller during day-time, and used to cover the over-night demand, whereas in winter a heat exchanger is used during the day to charge the tanks. Thermal energy has been stored in two chilled water tanks (with total capacity of 5000 L) or in two tanks (total volume 4000 L) containing two phase change materials (PCM): a PCM with melting point of 10 degrees C for refrigeration, and a PCM with melting temperature of 46 degrees C for heating. Our results show that the storing in PCM is more convenient, providing air-conditioning service for approximately 4 h 30 min in refrigeration, with a significant reduction of the electricity consumption with respect to the conventional system. The chilled water tanks can cover the demand for 4 h (scaled down to 3 h 12 min if the capacity is 4000 L), with even lower electric consumption. In winter, on the other hand, the tanks can cover fully the demand of overnight heating. Our results prove the viability of thermal storing, in particular using PCM, to extend the application solar cooling and heating to night-time, which is economically feasible, in a fully operational building.

Linear response theory relates the response of a system to a weak external force with its dynamics in equilibrium, subjected to fluctuations. Here, this framework is applied to financial markets; in particular we study the dynamics of a set of stocks from the NASDAQ during the last 20 years. Because unambiguous identification of external forces is not possible, critical events are identified in the series of stock prices as sudden changes, and the stock dynamics following an event is taken as the response to the external force. Linear response theory is applied with the log-return as the conjugate variable of the force, providing predictions for the average response of the price and return, which agree with observations, but fails to describe the volatility because this is expected to be beyond linear response. The identification of the conjugate variable allows us to define the perturbation energy for a system of stocks, and observe its relaxation after an event.