Simplified methodology for indoor environment designs

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Architecture, 2000.Includes bibliographical references (p. 231-237).Current design of the building indoor environment uses averaged single parameters such as air velocity, air temperature or contaminant concentration. This approach gives only general information about thermal comfort and indoor air quality, which is limiting for the design of energy efficient and healthy buildings. The design of these buildings requires sophisticated but practical tools that are not currently available, and the objective of this thesis is to develop such a tool. The development of the simple design tool had several phases. Each phase employed simplified models validated with measured data in order to assess model accuracy and reliability. The validation data was obtained from a state-of-the-art experimental facility at MIT. Based on the collected data, we first developed simplified boundary conditions for the diffuser jet flow, which is the key flow element in mechanically ventilated spaces. The boundary conditions employ resultant momentum from the supply diffusers without modeling the detailed diffuser geometry. Although simple, the models can simulate airflow from complex diffusers commonly used for air-conditioning with reasonable accuracy. Another simplification is the use of a zero-equation turbulence model to calculate indoor air distribution. The model uses the concept of eddy-viscosity and approximate turbulent viscosity with an algebraic equation. To test the turbulence model, an airflow program was developed. The program can simulate indoor airflow on a PC within several minutes, which is five to ten times faster than with the similar programs with a "standard" k-£ model. Finally, the airflow program was coupled with an energy analysis program. The combined program simultaneously analyzes internal heat transfer and air movement as well as the heat transfer through the building envelope. The impacts on the thermal comfort in the occupied zone are quantified, and we found that the thermal comfort in most cases is notby Jelena Srebric.Ph.D

Numerical Evaluation of the Local Weather Data Impacts on Cooling Energy Use of Buildings in an Urban Area

AbstractAccurate weather data plays an important role in the evaluation of building energy consumption in urban areas. The local air temperature and local wind speed can vary significantly due to the influence of microclimate conditions, while those parameters have a significant effect on energy demand especially in the summer. This study provides a new coupled numerical approach that building energy simulation (BES), using the airport weather data, transfers building surface temperature data to computational fluid dynamics (CFD) as the boundary conditions. In addition, the outdoor thermal environment is simulated using the CFD method and local weather data is calibrated and transferred to BES as the real-time meteorological data. A daily coupled simulation is performed for a building located in a specified urban density accounting for actual wind speed and direction. The comparison shows that the difference for daily building energy consumption is up to 2.5% using the airport weather data and local weather data. Therefore, accurate estimation of local weather data is necessary when on-site measured data is not available

Assessment of grain oil content stability in early maturing soybean genotypes

in the grain. The processing industry, as well as individual agricultural producers, pays special attention to these two parameters, setting requirements for varieties with high oil content for industrial processing, or varieties with high protein content for animal feed. Therefore, breeding practice is aimed at developing varieties not only of high yield but also varieties of improved grain quality. Soybean genotypes maintained in the collection of the Maize Research Institute Zemun Polje are characterized by a protein content ranging from 36.3% to 43.2%, and an oil content ranging from 15.6% to 22.0%. Both traits are of a complex quantitative nature, determined both by genetic factors and the influence of environmental conditions during their accumulation in the grain, as well as the interaction of genotype and environment. The aim of this study was to examine the value of genotype × environment interaction for oil content in soybean genotypes from the collection of Maize Research Institute Zemun Polje and to identify stable sources that can be utilized as starting material for breeding for oil content. The experiment included 14 genotypes of soybean from maturity group 00 (very early varieties). The field trials were set up over two years, at two locations (Zemun Polje and Pancevo), according to a completely randomized block design with three replications. After harvest, the oil content in the grain was measured on a NIRT device "Infraneo", Chopin Technologies. The linear-bilinear AMMI-1 model was applied to analyze the genotype × environment interaction for grain oil content. A large part of the variation (80.91%) of the genotype × environment interaction for the grain oil content in soybean genotypes was explained by the first interaction axis of the AMMI-1 model. The differences in the main effects of the examined environments were not large, since all environments had a value of oil content close to the general average. Four environments had a variable influence on the examined genotypes. For both locations, a positive interaction effect was found in 2012 and a negative interaction effect in 2011, with the genotypes tested in Zemun Polje in 2012 being the most unstable, while the genotypes tested in 2011 showed approximately equal stability at both locations. A number of genotypes (Canatto, Kabott, Olima, Gi 291 / 70-79, Krajina, Agassiz, Maple Presto and Luso) were distributed close to the stability line. Genotypes with above the average oil content and high stability (Maple Presto and Ljuso) deserved special attention, as well as the Agassiz genotype, which had the maximum average value of this parameter, and a small value of interaction with environments. Genotypes of low average values of oil content (Mini Soybeans and Progress) had very poor stability, which can be attributed to their divergent germplasm and specific response to environmental conditions that differ from the conditions in the region of their origin.Prerađivačka industrija kao i individualni poljoprivredni proizvođači obraćaju posebnu pažnju na ova dva parametra, postavljajući zahteve za sortama visokog sadržaja ulja za industrijsku preradu, ili sortama visokog sadržaja proteina za dobijanje stočne hrane. Stoga je selekcionerski rad usmeren je ka stvaranju sorti ne samo visokog prinosa već i sorti poboljšanog kvaliteta zrna. Genotipovi soje koji se čuvaju u kolekciji Instituta za kukuruz Zemun Polje odlikuju se sadržajem proteina koji varira od 36.3% do 43.2%, i sadržajem ulja u rasponu od 15.6% do22.0%. Oba svojstva su kompleksne kvantitativne prirode, determinisana kako naslednim faktorima tako i uticajem uslova spoljašnje sredine u vreme njihove akumulacije u zrnu, kao i interakcijom genotipa i spoljašnje sredine. Cilj ovog rada bio je da se ispita vrednost interakcije genotip × spoljašnja sredina za sadržaj ulja kod genotipova soje iz kolekcije Instituta za kukuruz Zemun Polje i otkriju stabilni izvori koji mogu poslužiti kao početni materijal za oplemenjivanje na sadržaj ulja. Eksperimentom je obuhvaćeno 14 genotipova soje grupe zrenja 00 (veoma rane sorte). Ogledi su postavljeni u toku dve godine, na dve lokacije (Zemun Polje i Pančevo), po potpuno slučajnom blok dizajnu u tri ponavljanja. Nakon žetve, sadržaj ulja u semenu izmeren je na uređaju NIRT tehnologije „Infraneo“, Chopin Technologies. Za analizu interakcije genotipa i spoljašnje sredine za sadržaj ulja u zrnu primenjen je linearno-bilinearni AMMI-1 model. Veliki deo varijacije (80,91%) interakcije genotipa i spoljašnje sredine za sadržaj ulja u zrnu ispitivanih genotipova soje objašnjen je prvom interakcijskom osom AMMI-1 modela. Razlike u glavnim efektima ispitivanih spoljašnjih sredina nisu bile velike, s obzirom da su sve sredine imale vrednost sadržaja ulja blizu opšteg proseka. Četiri spoljašnje sredine imale su varijabilan uticaj na ispitivane genotipove. Za oba lokaliteta utvrđen je pozitivan interakcijski efekat u 2012. i negativan interakcijski efekat u 2011. godini, pri čemu su genotipovi ispitivani u Zemun Polju 2012. godine bili najnestabilniji, dok su genotipovi ispitivani u toku 2011. godine pokazali približno jednaku stabilnost na obe lokacije Veći broj genotipova (Canatto, Kabott, Olima, Gi 291/70-79, Krajina, Agassiz, Maple Presto i Ljuso) bio je raspoređen blizu linije stabilnosti, pri čemu posebnu pažnju zaslužuju genotipovi iznad posečnog sadržaja ulja i visoke stabilnosti (Maple Presto i Ljuso) kao i genotip Agassiz, koji je imao maksimalnu prosečnu vrednost ovog parametra, i malu vrednost interakcije sa spoljašnjim sredinama. Genotipovi niskih prosečnih vrednosti sadržaja ulja (Mini Soja i Progres) imali su veoma slabu stabilnost, što se može pripisati njihovoj divergentnoj germplazmi i specifičnoj reakciji na uslove ispitivanja koji se razlikuju u odnosu na uslove regiona u kojem su ove sorte selekcionisane

Multivariate analysis of agronomic traits in mid-season soybean varieties

Principal Component Analysis (PCA) is a useful tool for processing multiple data, which are often encountered in breeding practice. This method is suitable for the evaluation of genotypes on the basis of multiple traits and graphical presentation of relationships between traits. This study included 16 soybean mid-season genotypes (maturity group I), originated from different regions of the world, maintained in soybean collection of Maize Research Institute Zemun Polje. Field trials were carried out at two locations, during two years, according to a RCB design with three replications. The genotypes were evaluated in respect to eight major agronomic traits: PH – plant height, NN – node number, PN – pod number, SN – seed number, TSW – 1000 seed weight, SYP – seed yield per plant, PROT – protein content, OIL – oil content. First two PCA axes encompassed a large portion of the variance of standardized data (75,9%). Biplot distinguished genotypes of potential importance for various breeding targets. Two genotypes stood out with the largest 1000 seed weight. One variety formed a larger number of pods and the seed number per plant as compared to the group average, achieving the highest grain yield per plant. Two genotypes were among the most productive ones, with a larger number of pods as well as a higher 1000 seed weight, compared to the average. The most promising variety was Laura, which had a high yield and higher protein content than the average, and could be used as a potential germplasm source for the simultaneous improvement of both traits. Correlations among traits determined by PC biplot were in accordance with Pearson’s correlation coefficients

A radiative cooling structural material.

Reducing human reliance on energy-inefficient cooling methods such as air conditioning would have a large impact on the global energy landscape. By a process of complete delignification and densification of wood, we developed a structural material with a mechanical strength of 404.3 megapascals, more than eight times that of natural wood. The cellulose nanofibers in our engineered material backscatter solar radiation and emit strongly in mid-infrared wavelengths, resulting in continuous subambient cooling during both day and night. We model the potential impact of our cooling wood and find energy savings between 20 and 60%, which is most pronounced in hot and dry climates

Advanced computational modeling for in vitro nanomaterial dosimetry

Background: Accurate and meaningful dose metrics are a basic requirement for in vitro screening to assess potential health risks of engineered nanomaterials (ENMs). Correctly and consistently quantifying what cells “see,” during an in vitro exposure requires standardized preparation of stable ENM suspensions, accurate characterizatoin of agglomerate sizes and effective densities, and predictive modeling of mass transport. Earlier transport models provided a marked improvement over administered concentration or total mass, but included assumptions that could produce sizable inaccuracies, most notably that all particles at the bottom of the well are adsorbed or taken up by cells, which would drive transport downward, resulting in overestimation of deposition. Methods: Here we present development, validation and results of two robust computational transport models. Both three-dimensional computational fluid dynamics (CFD) and a newly-developed one-dimensional Distorted Grid (DG) model were used to estimate delivered dose metrics for industry-relevant metal oxide ENMs suspended in culture media. Both models allow simultaneous modeling of full size distributions for polydisperse ENM suspensions, and provide deposition metrics as well as concentration metrics over the extent of the well. The DG model also emulates the biokinetics at the particle-cell interface using a Langmuir isotherm, governed by a user-defined dissociation constant, KD, and allows modeling of ENM dissolution over time. Results: Dose metrics predicted by the two models were in remarkably close agreement. The DG model was also validated by quantitative analysis of flash-frozen, cryosectioned columns of ENM suspensions. Results of simulations based on agglomerate size distributions differed substantially from those obtained using mean sizes. The effect of cellular adsorption on delivered dose was negligible for KD values consistent with non-specific binding (> 1 nM), whereas smaller values (≤ 1 nM) typical of specific high-affinity binding resulted in faster and eventual complete deposition of material. Conclusions: The advanced models presented provide practical and robust tools for obtaining accurate dose metrics and concentration profiles across the well, for high-throughput screening of ENMs. The DG model allows rapid modeling that accommodates polydispersity, dissolution, and adsorption. Result of adsorption studies suggest that a reflective lower boundary condition is appropriate for modeling most in vitro ENM exposures. Electronic supplementary material The online version of this article (doi:10.1186/s12989-015-0109-1) contains supplementary material, which is available to authorized users

Towards an integrated computational method to determine internal spaces for optimum environmental conditions

Computational Fluid Dynamics tools and Response Surface Methodology optimization techniques were coupled for the evaluation of an optimum window opening design that improves the ventilation efficiency in a naturally-ventilated building. The multi-variable optimization problem was based on Design of Experiments analysis and the Central Composite Design method for the sampling process and estimation of quadratic models for the response variables. The Screening optimization method was used for the generation of the optimal design solution. The generated results indicated a good performance of the estimated response surface revealing the strength correlations between the parameters. Window width was found to have greater impact on the flow rate values with correlation coefficient of 73.62%, in comparison to the standard deviation 55.68%, where the window height prevails with correlation coefficient of 96.94% and 12.35% for the flow rate. The CFD results were validated against wind tunnel experiments and the optimization solution was verified with simulation runs, proving the accuracy of the methodology followed, which is applicable to numerous environmental design problems

Modeling sustainability : Population, inequality, consumption, and bidirectional coupling of the Earth and human systems

Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. We argue that in order to understand the dynamics of either system, Earth SystemModels must be coupled with Human SystemModels through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as United Nations population projections.This makes current models likely to miss important feedbacks in the real Earth-Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models.The importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth-Human system models for devising effective science-based policies and measures to benefit current and future generations

Real-time flow simulation of indoor environments using lattice Boltzmann method

A novel lattice Boltzmann method (LBM) based 3D computational fluid dynamics (CFD) technique has been implemented on the graphics processing unit (GPU) for the purpose of simulating the indoor environment in real-time. We study the time evolution of the turbulent airflow and temperature inside a test chamber and in a simple model of a four-bed hospital room. The predicted results from LBM are compared with traditional CFD based large eddy simulations (LES). Reasonable agreement between LBM results and LES method is observed with significantly faster computational times

Optimization of air distribution mode coupled interior design for civil aircraft cabin

The airflow distribution and thermal comfort of human beings in civil aircraft cabin are influenced by many factors such as the ventilation mode, ventilation air volume, and supply air temperature and so on. Among these factors, the choice of ventilation mode in the civil aircraft cabin is also restricted by the interior and aesthetic designs. Yet few researches noticed the impact of these designs on cabin air distribution. In this paper, an optimization design method for the air distribution mode of civil aircraft will be discussed based on Computational Fluid Dynamic (CFD) method and Micro-Genetic Algorithm (Micro-GA). Two interior design structures with different luggage bin and light band will be used to investigate their influence on the design of air distribution mode. In this optimization, the position of air supply inlets and the supply air angle are defined as the optimization variables. The Predicted Mean Vote (PMV) and the air age are specially chosen as the objective functions. The relevant regulations for cabin temperature uniformity are determined as the thermal constraint conditions. The study results show that the presented method can ensure the convergence of optimization process. The Pareto Optimal Frontiers (POFs) can be obtained from this multi-objective optimization. The POFs can present the relationship of two objective functions. The preferred air distribution mode coupled different interior designs can be efficiently recommended from the optimization results