Semi-transparent Photovoltaic Thermal Greenhouse System Combined with Earth Air Heat Exchanger for Hot Climatic Condition

Semi-transparent photovoltaic thermal (SPVT) greenhouse system combined with an earth air heat exchanger (EAHE) has been developed to make the system sustainable. The system is designed to cultivate plants in a hot climatic condition, where green net is provided which bifurcates the enclosed space of the greenhouse into zone-1 and zone-2, and this green net cuts the solar radiation incident on the plants. The influence of air changes in zone-1, mass flow rate of air flowing through EAHE, and packing factor on PV cell, air of the greenhouse, and the plant temperatures is investigated for a typical harsh summer day by using periodic model of these parameters. Further, for a holistic performance assessment of this SPVT greenhouse, exergy, thermal load leveling, and decrement factor are evaluated. Results indicate that the optimum temperature range for plant growth (30 °C- 37 °C) within the greenhouse can be achieved through a combination of ventilation in zone-1 and integration of EAHE. The temperature of plants reduced by 9 °C for 30 air changes in zone-1, and the temperature reduces further by 24 °C when EAHE having a flow rate of 0.5 kg/s is operated. The SPVT greenhouse system also generates 128 kWh of daily overall exergy that makes the system sustainable.

First-principles modeling of the infrared spectrum of Fe- and Al-bearing lizardite

The theoretical vibrational properties of a series of Fe- and Al-bearing lizardite models have been determined at the density functional theory level. Each periodic model displays a single cationic impurity substituted at an octahedral or tetrahedral site of a supercell of lizardite (Mg3Si2O5(OH)4) containing 162 atoms. The isovalent Fe2+ for Mg2+ substitution has been considered, as well as the heterovalent substitution of Fe3+ or Al3+ for Mg2+ or Si4+. Comparison of the theoretical absorption spectra with previously reported experimental spectra of natural and laboratory-grown lizardite samples allows us to propose an interpretation for most of the observed bands. Although the identification of specific bands related to octahedral Fe2+ in FTIR spectra is challenging, broad bands at 3584 and 3566 cm−1 reflect the occurrence of octahedral Al3+ and Fe3+, respectively, in the natural samples. These broad bands likely overlap with potential contribution related to tetrahedral Al3+. It is suggested that the modification of the H-bonding pattern related to the incorporation of trivalent ions at tetrahedral sites has an overall broadening effect on the interlayer-OH stretching bands of lizardite.

Vacancies in the molecular crystal of 2-(2'-hydroxyphenyl)benzothiazole

Structure of molecular units is calculated for the periodic model corresponding to the crystal lattice of 2-(2'-hydroxyphenyl)benzothiazole with vacancies. 2-(2' -hydroxyphenyl)benzothiazole is a luminescent organic substance undergoing excited state intramolecular proton transfer. The calculations are performed with density-functional based tight-binding methods usding Van der Waals interaction empirical correction. It is found that the dihedral angles formed by benzothiazole and phenol parts of the molecules deviate in the vicinity of the vacancy. The vacancy provides enough space for non-planar conformation of the molecules in the ground state. At the same time the increase in energy of the periodic structure with the vacancies caused by appearance of the non-planar conformation is larger than the corresponding increase in the isolated molecule.

An adaptive MPC scheme for energy-efficient control of building HVAC systems

An autonomous adaptive MPC architecture is presented for control of heating, ventilation and air condition (HVAC) systems to maintain indoor temperature while reducing energy use. Although equipment use and occupant changes with time, existing MPC methods are not capable of automatically relearning models and computing control decisions reliably for extended periods without intervention from a human expert. We seek to address this weakness. Two major features are embedded in the proposed architecture to enable autonomy: (i) a system identification algorithm from our prior work that periodically re-learns building dynamics and unmeasured internal heat loads from data without requiring re-tuning by experts. The estimated model is guaranteed to be stable and has desirable physical properties irrespective of the data; (ii) an MPC planner with a convex approximation of the original nonconvex problem. The planner uses a descent and convergent method, with the underlying optimization problem being feasible and convex. A year long simulation with a realistic plant shows that both of the features of the proposed architecture - periodic model and disturbance update and convexification of the planning problem - are essential to get performance improvement over a commonly used baseline controller. Without these features, long-term energy savings from MPC can be small while with them, the savings from MPC become substantial.

APPLICATION OF PERIODIC REVIEW INVENTORIES MODEL IN A TYPICAL MEXICAN FOOD COMPANY

The Mexican family companies must face the challenges of market volatility with greater recurrence, forcing them to use effective tools and models for the proper management of their organizations and inherent activities, such as inventory management. Therefore, this research was carried out at “Moles Santa Monica”, a typical food company located in the city of Puebla, Mexico. This enterprise has reflected a high variability in the administration of its inventories, with a Coefficient of Variation (CV) greater than 0.2 in most of their portfolio products. In this way, the objective of this study was to propose an inventory management model that might reduce the shortages and overstock, and also; improves its performance and profitability when it is managed. The applied methods were Pareto and ABC model to choose correctly the best seller company products. The inventory management model chosen was the periodic review (R, S) as well, for being the most effective and the one that best suited the circumstances of the company in question. Three of the portfolio products were studied (MPP10, MPC10 and COP10) due to they are the most representative in incomes and valuables for the company managers. The results allowed us to propose the review periodic model (R), the optimal quantity of units to produce (Q), the safety stock (Ss) and the maximum inventory (S) for each product. We conclude that this model will help the company to face the uncertainty of the demand. Finally, we include limitations and future studies.

An Efficient Hybrid Approach for Scheduling the Train Timetable for the Longer Distance High-Speed Railway

Compared with other modes of transportation, a high-speed railway has energy saving advantages; it is environmentally friendly, safe, and convenient for large capacity transportation between cities. With the expansion of the high-speed railway network, the operation of high-speed railways needs to be improved urgently. In this paper, a hybrid approach for quickly solving the timetable of high-speed railways, inspired by the periodic model and the aperiodic model, is proposed. A space–time decomposition method is proposed to convert the complex passenger travel demands into service plans and decompose the original problem into several sub-problems, to reduce the solving complexity. An integer programming model is proposed for the sub-problems, and then solved in parallel with CPLEX. After that, a local search algorithm is designed to combine the timetables of different periods, considering the safety operation constraints. The hybrid approach is tested on a real-world case study, based on the Beijing–Shanghai high-speed railway (HSR), and the results show that the train timetable calculated by the approach is superior to the real-world timetable in many indexes. The hybrid approach combines the advantages of the periodic model and the aperiodic model; it can deal with the travel demands of passengers well and the solving speed is fast. It provides the possibility for flexible adjustment of a timetable and timely response to the change of passenger travel demands, to avoid the waste of transportation resources and achieve sustainable development.