Uncertainty and sensitivity analyses of operational errors in air handling units and unexpected user behavior for energy efficiency and thermal comfort

Resource scarcity and anthropogenic climate change require the reduction of performance gaps in existing buildings. In addition to unexpected user behavior, performance gaps are primarily caused by the technical gap due to operational errors in building technology. The main objective of this paper is to quantify model input uncertainty incorporating uncertain boundary conditions in terms of operational errors using thermo-dynamic building performance simulations and to identify the most relevant input parameters for the performance gaps in air conditioning systems by means of sensitivity analyses. Model input uncertainty is stochastically determined using Monte-Carlo Simulations to calculate the target values “primary energy demand” as well as “over- and under-temperature degree hours” for an office building. Selected parameters are simulated in a specific uncertainty and sensitivity analyses using the Sobol’ and Jansen estimators, which distinguish between a direct influence on the target variables and interactions between the parameters. The methodology requires a selection process, which is carried out as part of relative uncertainty and relative sensitivity analyses. Furthermore, the operational errors are compared with construction factors as well as building physics inputs and design parameters for building technology systems to show their reciprocal effects as part of a comprehensive investigation. The main findings of this paper are that operational errors in air conditioning systems play an essential role in decreasing energy efficiency and thermal comfort, but do not warrant the significance of certain construction factors as well as setpoints in building technology. Moreover, the impact of operational errors on thermal overheating of the building investigated is minor compared to other targets that cause greater model input uncertainty.

Development and Application of a Mechanistic Cooling and Freezing Model of the Spin Freezing Step within the Framework of Continuous Freeze-Drying

During the spin freezing step of a recently developed continuous spin freeze-drying technology, glass vials are rapidly spun along their longitudinal axis. The aqueous drug formulation subsequently spreads over the inner vial wall, while a cold gas flow is used for cooling and freezing the product. In this work, a mechanistic model was developed describing the energy transfer during each phase of spin freezing in order to predict the vial and product temperature change over time. The uncertainty in the model input parameters was included via uncertainty analysis, while global sensitivity analysis was used to assign the uncertainty in the model output to the different sources of uncertainty in the model input. The model was verified, and the prediction interval corresponded to the vial temperature profiles obtained from experimental data, within the limits of the uncertainty interval. The uncertainty in the model prediction was mainly explained (>96% of uncertainty) by the uncertainty in the heat transfer coefficient, the gas temperature measurement, and the equilibrium temperature. The developed model was also applied in order to set and control a desired vial temperature profile during spin freezing. Applying this model in-line to a continuous freeze-drying process may alleviate some of the disadvantages related to batch freeze-drying, where control over the freezing step is generally poor.

Linkages Perekonomian Bali

Berbagai studi telah dilakukan untuk menganalisis dampak pengganda dari perekonomian Bali. Namun, studi-studi tersebut umumnya berfokus pada keterkaitan antar sektor menggunakan model Input-Output (IO). Padahal, perekonomian antar wilayah dapat saling bergantung melalui berbagai macam eksternalitas dan jaringan rantai suplai. Studi ini menganalisis perekonomian Bali tidak hanya berdasarkan hubungan antar sektor, namun juga mempertimbangkan hubungan ekonomi Bali dengan provinsi lainnya. Model yang digunakan adalah Inter Regional Input Output (IRIO). Tabel IRIO berukuran 17 industri x 34 provinsi diperoleh dari Badan Pusat Statistik. Hasil analisis menunjukkan bahwa terdapat beberapa industri unggulan di Provinsi Bali, yaitu Listrik dan Gas, Transportasi dan Pergudangan, Informasi dan Komunikasi, dan Jasa Perusahaan. Industri Listrik dan Gas memiliki keterkaitan antar sektor dan dampak output yang paling besar diantara industri-industri di Provinsi Bali. Selanjutnya, analisis antar wilayah menunjukkan bahwa shock permintaan akhir di Provinsi Bali berdampak besar terhadap perekonomian provinsi-provinsi di Pulau Jawa, khususnya Jawa Timur. Di sisi lain, perekonomian Bali sangat dipengaruhi oleh shock permintaan akhir di Provinsi Nusa Tenggara Barat.

Supplemental Material: Seismicity recorded in hematite fault mirrors in the Rio Grande rift

Contains detailed microscopy and thermochronology methodologies, (U-Th)/He data tables, grain size measurements, thermal history model input table, and figures.<br>

Supplemental Material: Seismicity recorded in hematite fault mirrors in the Rio Grande rift

Contains detailed microscopy and thermochronology methodologies, (U-Th)/He data tables, grain size measurements, thermal history model input table, and figures.<br>

Watershed subdivision and weather input effect on streamflow simulation using SWAT model

In watershed modeling research, it is practical to subdivide a watershed into smaller units or sub-watersheds for modeling purposes. The ability of a model to simulate the watershed system depends on how well watershed processes are represented by the model and how well the watershed system is described by model input. This study is conducted to evaluate the impact of watershed subdivision and different weather input datasets on streamflow simulations using the soil and water assessment tool model. For this purpose, Cuhai-Bakonyér watershed was chosen as a study area. Two climate databases and four subdivision variations levels were evaluated. The model streamflow predictions slightly effected by subdivision impact. The climate datasets showed significant differences in streamflow predictions.

Uncertainty analysis of model inputs in riverine water temperature simulations

Simulation models are often affected by uncertainties that impress the modeling results. One of the important types of uncertainties is associated with the model input data. The main objective of this study is to investigate the uncertainties of inputs of the Heat-Flux (HFLUX) model. To do so, the Shuffled Complex Evolution Metropolis Uncertainty Algorithm (SCEM-UA), a Monte Carlo Markov Chain (MCMC) based method, is employed for the first time to assess the uncertainties of model inputs in riverine water temperature simulations. The performance of the SCEM-UA algorithm is further evaluated. In the application, the histograms of the selected inputs of the HFLUX model including the stream width, stream depth, percentage of shade, and streamflow were created and their uncertainties were analyzed. Comparison of the observed data and the simulations demonstrated the capability of the SCEM-UA algorithm in the assessment of the uncertainties associated with the model input data (the maximum relative error was 15%).

Sensitivity of Food-Based Recommendations Developed Using Linear Programming to Model Input Data in Young Kenyan Children

Food-based recommendations (FBR) developed using linear programming generally use dietary intake and energy and nutrient requirement data. It is still unknown to what extent the availability and selection of these data affect the developed FBR and identified problem nutrients. We used 24 h dietary recalls of 62 Kenyan children (4–6 years of age) to analyse the sensitivity of the FBR and problem nutrients to (1) dietary intake data, (2) selection criteria applied to these data and (3) energy and nutrient requirement data, using linear programming (Optifood©), by comparing a reference scenario with eight alternative scenarios. Replacing reported by estimated consumption frequencies increased the recommended frequencies in the FBR for most food groups while folate was no longer identified as a problem nutrient. Using the 10–90th instead of the 5–95th percentile of distribution to define minimum and maximum frequencies/week decreased the recommended frequencies in the FBR and doubled the number of problem nutrients. Other alternative scenarios negligibly affected the FBR and identified problem nutrients. Our study shows the importance of consumption frequencies for developing FBR and identifying problem nutrients by linear programming. We recommend that reported consumption frequencies and the 5–95th percentiles of distribution of reported frequencies be used to define the minimum and maximum frequencies.

HYBRID EXPERIMENTAL AND NUMERICAL CHARACTERIZATION OF THE 3D RESPONSE OF WOVEN POLYMER MATRIX COMPOSITES

The need for advanced material models to simulate the deformation, damage, and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased usage in the aerospace and automotive industries. The purpose of this work is to characterize carbon epoxy fabrics for composite material models that rely on a large number of input parameters to define their nonlinear and 3D response; e.g. elastic continuum damage mechanics models or plasticity damage models [1, 2]. It is challenging to obtain large sets of experimental stress-strain curves, therefore, careful selection of physical experiments that exhibit nonlinear behavior is done to significantly reduce the cost of generating threedimensional material databases. For this work, plain weave carbon fabrics with 3k and 12k tows are manufactured by VARTM. Testing is done using MTS hydraulic test frames and 2D digital image correlation (DIC) to obtain experimental stress-strain curves for in-plane tension and shear as well as transverse shear. For cases where actual experimental data is either not available or difficult to obtain, the required model input is virtually generated using the NASA Glenn developed Micromechanics Analysis Method/Generalized Method of Cells (MAC/GMC) code. A viscoplastic polymer model is calibrated and utilized to model the matrix constituent within a repeating unit cell (RUC) of a plain weave carbon fiber fabric. Verification and validation of this approach is done using MAT213, a tabulated orthotropic material model in the finite element code LS-DYNA, which relies on 12 input stress-strain curves in various coordinate directions [2]. Based on the model input generated by the micromechanics analyses in combination with available experimental data, a series of coupon level verification and validation analyses are carried out using the MAT 213 composite model.

Supplemental Material: Thermodynamic limits for assimilation of silicate crust in primitive magmas

Supplemental discussion on the MCS model parameters, and all model input and output.<br>