Main Sources Of Uncertainty Research Articles

A Novel Parallel-Plate Dielectric Resonator Method for Broadband Complex Permittivity Measurement in the Millimeter-Wave Bands

This article proposes a novel measurement method based on parallel-plate dielectric resonator (PPDR) for determining complex permittivity of low-loss dielectric materials over a wide frequency range. Two 1.0-mm coaxial probes are placed symmetrically as a coupling structure in the center of top and bottom of the PPDR, and only the TM <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{\mathrm{0np}}$</tex-math> </inline-formula> resonant modes will be selectively excited. For each value of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p$</tex-math> </inline-formula> , the resonator will operate over a specific frequency range, within which there are usually multiple frequency points available for testing. Based on this unique feature, dielectric constants of cylindrical or disk-shaped samples can be measured from less than 20 up to 110 GHz by utilizing TM <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{\mathrm{0np}}$</tex-math> </inline-formula> high-order modes. Rigorous analysis of the PPDR based on the electromagnetic field matching method is carried out and verified numerically. Moreover, the PPDR method is further validated experimentally by measuring several specimens processed from well-known materials, the main sources of measurement uncertainty are also analyzed in detail, and some recommendations are made accordingly. The results show that the PPDR method can perform high-accuracy measurement of complex permittivity in the millimeter-wave bands, even when the sample thickness exceeds the maximum value limited by the current state of the art.

Representation of soil hydrology in permafrost regions may explain large part of inter-model spread in simulated Arctic and subarctic climate

Abstract. The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone, with differences in model structure and parametrizations being one of the main sources of uncertainty. One particularly challenging aspect in modelling is the representation of terrestrial processes in permafrost-affected regions, which are often governed by spatial heterogeneity far below the resolution of the models' land surface components. Here, we use the Max Planck Institute (MPI) Earth System Model to investigate how different plausible assumptions for the representation of permafrost hydrology modulate land–atmosphere interactions and how the resulting feedbacks affect not only the regional and global climate, but also our ability to predict whether the high latitudes will become wetter or drier in a warmer future. Focusing on two idealized setups that induce comparatively “wet” or “dry” conditions in regions that are presently affected by permafrost, we find that the parameter settings determine the direction of the 21st-century trend in the simulated soil water content and result in substantial differences in the land–atmosphere exchange of energy and moisture. The latter leads to differences in the simulated cloud cover during spring and summer and thus in the planetary energy uptake. The respective effects are so pronounced that uncertainties in the representation of the Arctic hydrological cycle can help to explain a large fraction of the inter-model spread in regional surface temperatures and precipitation. Furthermore, they affect a range of components of the Earth system as far to the south as the tropics. With both setups being similarly plausible, our findings highlight the need for more observational constraints on the permafrost hydrology to reduce the inter-model spread in Arctic climate projections.

Uncertainty Quantification of Laminar–Turbulent Transition on Airfoil and Fuselage

The effect of uncertainty in Reynolds-averaged Navier–Stokes (RANS) simulations is determined through the application of uncertainty quantification (UQ). In this study, the sensitivity of aerodynamic coefficients to uncertainty in the freestream turbulence intensity (FSTI) and surface roughness is computed for an airfoil (SC1095) and a rotorcraft fuselage model (Rotor-Body-Interaction-Mod7). A laminar–turbulent transition model has been extended to consider roughness-induced transition by incorporating an existing roughness-induced transition model. The current UQ analysis is based on the Monte Carlo method with the Gaussian distributions of uncertain input parameters. A surrogate model allows for incorporating the results of intensive RANS simulations into the Monte Carlo method. The surrogate model is generated using a cubic interpolation for a single-uncertain parameter or a radial basis function for multiple-uncertain parameters. The stochastic standard deviation is measured using combined FSTI and roughness uncertainties. The standard deviation of each aerodynamic coefficient depends on flow conditions (angle of attack, mean FSTI, and mean roughness) and the transition type (natural or separation-induced). The main source of output uncertainty is identified between the unknown FSTI and roughness under various flow conditions.

Bio-optical properties of South Brazil Bight coastal waters and implications for satellite chlorophyll-a concentration retrieval

ABSTRACT Retrieving chlorophyll-a concentration (Chla) from remote-sensing data is especially challenging in coastal regions because of the presence of other co-dominant optically significant constituents (OSCs). In this study, we characterize bio-optical variability at a fixed coastal time series station in the South Brazil Bight (SBB), the ANTARES-Ubatuba site (São Paulo, Brazil) from radiometric measurements and water sample analyses, and evaluate the performance of ocean colour (OC) algorithms for Chla retrieval. In situ Chla and the spectral absorption of phytoplankton (aph), detritus, and coloured dissolved organic matter (CDOM), as well as the above-water remote-sensing reflectance (Rrs) were obtained from 2004 to 2019 at a quasi-monthly sampling frequency. Chla exhibited high variability, with a standard deviation twice as large as the mean (1.0 ± 1.83 mg m−3), and values ranging from 0.18 mg m−3 up to 18.09 mg m−3 during episodic bloom events. CDOM was the dominant OSC contributing to the absorption coefficient at 443 nm all-year round, suggesting the influence of continental sources, even though the station is located at the external limit of the inner shelf (40 m). Two optical water types were defined: one composed mainly of ‘blue’ waters with lower concentrations of the OSCs and another of ‘green’ waters with higher concentrations of OSCs. Despite the CDOM spectral dominance, the empirical OCx performed reasonably well with a positive bias for both in situ (17–25%) and satellite (25–31%) Chla retrievals. The performance was slightly better using the 3-band OC3 algorithm by selecting the best band ratio with lower influence of CDM (CDOM + detritus) absorption (Rrs (490/555)). The main sources of uncertainty were caused by higher CDM proportions and phytoplankton-specific absorption, yielding positive biases on the OC3 retrievals. The results suggest that standard satellite products of Chla can be used (with some caution) to monitor and study the dynamics of the phytoplankton biomass within the region, knowing the expected uncertainties.

Evaluating uncertainty in climate change impacts on peak discharge and flood volume in the Qaran Talar watershed, Iran

Abstract This study evaluates the effects of climate change (CC) on runoff properties over the case study of the Qaran Talar watershed located in Iran. To consider the two main sources of uncertainty, i.e., Greenhouse Gases emission (GHG) scenarios and outputs of Atmosphere-Ocean General Circulation Models (AOGCMs), a daily rainfall time series was generated for two future periods (2021-2050 and 2070-2099) at three risk levels of 0.1, 0.25 and 0.50. 22 AOGCMs outputs following two emission scenarios (RCP4.5 and RCP8.5) were used. The results showed that the uncertainty of climate change scenarios was primarily owing to the uncertainty of GCMs outputs. Regarding the 2021-2050 period, under both emission scenarios, the increases in peak discharge and flood volume (FV) were estimated to reach 70, 50, and 30% at three risk levels of 0.1, 0.25 and 0.50, respectively, compared to the recent past period. As the current century draws to a close, the difference between the results of the two emission scenarios becomes apparent so that in the far-future period (2070-2099), the RCP8.5 scenario estimates and FV more than the RCP4.5 scenario does. Additionally, it was found that the uncertainty caused by AOGCMs was more than that by GHG emission scenarios.

Assessing the major sources of uncertainty in supply chains: survey

Reducing uncertainty in the supply chain (SC) is probably one of the major difficulties that the company must solve. Indeed, the SC is currently under enormous pressure and the decision-making process is frequently confronted with varied settings while making decisions due to the degree of uncertainty. The purpose of this study is to investigate the main major sources of uncertainty in SC. The study also examines the practices adopted to reduce uncertainty and enhance forecasting accuracy. A survey was carried out. Questionnaires were distributed amongst the managerial staff located in Morocco and other countries. We collected work e-mail addresses of managerial staff managerial working in SCs that operate in mass production and also in large-scale distribution and invited them to participate in an anonymous online survey. The questionnaire was designed to assess respondents' views about the main sources of uncertainty in SC and how they do to reduce it. Findings indicate that uncertainty occurs in any SC process, but the main uncertain prosses are procurement, supply planning, and demand forecasting. In addition, uncertainty comes from external and internal factors. Moreover, the decision-making mode, SC partnership, and risk contract have an important impact on the occurrence of uncertainty in the SC.

Determination of Melamine Uncertainty Assessment in Frozen Drinks

The uncertainty assessment of melamine in frozen drinks by high-performance liquid chromatography, According to the basic methods and procedures stipulated in the Assessment and presentation of Measurement Uncertainties and the Guidelines for the Assessment of Uncertainty in Chemical Analysis, The main sources of influence uncertainty were analyzed, and the assessment method for determining melamine uncertainty in frozen drinks was established. The results show that the results of (0.661 mg/kg ± 0.03, <i>k</i>=2) affect the determination of melamine uncertainty in frozen drinks, Uncertainty introduced by the fitted curve, the standard curve preparation process, the measurement repeatability, the Sample volume, the standard purity, Standard weighing and the sample amount. The model provides a reference for the uncertainty assessment of melamine in frozen drinks According to it, At the same time, in the daily detection and weighing, the measurement activities can be used to control the fitting curve and the standard solution preparation process, in order to reduce the measurement uncertainty, improve the accuracy of the test results, the compliance of the measurement results is important.

Nuclear data uncertainty influence on the breeding ratio in sodium-cooled fast reactor systems

Nuclear data are a main uncertainty source in neutron transport simulations making their consideration in reactor safety necessary. This arises anew with the state-of-the-art reactors known as Generation IV. Some of the reactors suggests providing the reactivity margin below the effective delayed neutron fraction excluding prompt criticality accidents, and the breeding ratio is the key factor in this. Consequently, assessing a degree of the breeding ratio accuracy is of interest. Therefore, in this work, the breeding ratio uncertainties are analyzed by performing a sensitivity and uncertainty analysis of the MET1000 and MOX3600 models with respect to nuclear data using SCALE. As a result, the breeding ratio uncertainties are obtained approximately equal to 2% as the main contributors are 239Pun,γ, 238Un,γ, and 238Un,n'. The uncertainty sources between the models are compared, and 16O preponderantly increases the total uncertainty not directly by its uncertainty but by its impact on the spectrum.

Stochastic schemes for the perturbation of the atmospheric boundary conditions in ocean general circulation models

Advancing the representation of uncertainties in ocean general circulation numerical models is required for several applications, ranging from data assimilation to climate monitoring and extended-range prediction systems. The atmospheric forcing represents one of the main uncertainty sources in numerical ocean models. Here, we formulate and revise different approaches to perturb the air-sea fluxes used within the atmospheric boundary conditions. In particular, perturbation of the fluxes is performed either through i) stochastic modulation of the air-sea transfer coefficients; ii) stochastic modulation of the air-sea flux tendencies; iii) coarse-graining of stochastic sub-grid computation of the fluxes; or iv) multiple bulk formulas. The schemes are implemented and tested in the NEMO4 ocean model, implemented at an eddy-permitting resolution on a domain covering the North Atlantic and Arctic oceans and the Mediterranean Sea. A series of 22-year 4-member ensemble experiments with different stochastic schemes are performed and analyzed for the period 2000-2021, and results are compared in terms of the ensemble mean and, when applicable, ensemble spread of the principal oceanic diagnostics. Results indicate that the schemes, in general, can significantly improve some verification skill scores (e.g. against drifter current speed, SST analyses, and hydrographic profiles) and, in some cases, enhance the mesoscale activity and weaken the large-scale circulation. The response, however, is different depending on the specific scheme, whose choice thus depends on the target application, as detailed in the paper. These findings foster the adoption of these schemes in both extended-range operational ocean forecasts and coupled long-range climate prediction systems, where the boundary conditions perturbations may contribute to performance increases.

Fluorescence Quantum Yield Standards for the UV/Visible/NIR: Development, Traceable Characterization, and Certification

The rational design of next generation molecular and nanoscale reporters and the comparison of different emitter classes require the determination of the fluorometric key performance parameter fluorescence quantum yield (Φf), i.e., the number of emitted photons per number of absorbed photons. Main prerequisites for reliable Φf measurements, which are for transparent luminophore solutions commonly done relative to a reference, i.e., a fluorescence quantum yield standard of known Φf, are reliable and validated instrument calibration procedures to consider wavelength-, polarization-, and time-dependent instrument specific signal contributions, and sufficiently well characterized fluorescence quantum yield standards. As the standard's Φf value directly contributes to the calculation of the sample's Φf, its accuracy presents one of the main sources of uncertainty of relative Φf measurements. To close this gap, we developed a first set of 12 fluorescence quantum yield standards, which absorb and emit in the wavelength region of 330-1000 nm and absolutely determined their Φf values with two independently calibrated integrating sphere setups. Criteria for standard selection and the configuration of these novel fluorescence reference materials are given, and the certification procedure is presented including homogeneity and stability studies and the calculation of complete uncertainty budgets for the certified Φf values. The ultimate goal is to provide the community of fluorescence users with available reference materials as a basis for an improved comparability and reliability of quantum yield data since the measurement of this spectroscopic key property is an essential part of the characterization of any new emitter.

Multiagent Reinforcement Learning for Project-Level Intervention Planning under Multiple Uncertainties

Reinforcement learning (RL) has recently been adopted by infrastructure asset management (IAM) researchers for adding flexibility regarding uncertainties in preventive actions decision-making. However, this relatively recent line of research has not incorporated other sources of uncertainties, such as hazards apart from deterioration patterns, nor has such research considered managerial aspects of IAM, such as stakeholders’ utilities. This paper aims to provide a holistic framework that draws upon recent developments in IAM systems and microworlds, employs RL model training, and considers deterioration, hazards, and cost fluctuations as the main sources of uncertainties while also adopting managerial aspects into decision-making. Consistent with the existing practice of IAM, this framework brings flexibility in the face of uncertainties to the IAM decision-making process. Multi-agent RL models based on deep Q networks and actor-critic models are constructed and trained for taking intervention actions regarding elements of a real bridge in Indiana through its life cycle. Both models could lead to higher expected utilities and lower costs compared to the optimal maintenance, rehabilitation, and reconstruction (MRR) plans obtained by Monte Carlo simulation and heuristic optimization algorithms. The proposed framework can assist decision-making bodies and managers in the IAM domain with making updateable optimal and more realistic decisions based on the updated state of various complex uncertainties in a negligible amount of time.

Using Lagrangian relaxation to locate hydrogen production facilities under uncertain demand: a case study from Norway

Hydrogen is considered a solution to decarbonize the transportation sector, an important step to meet the requirements of the Paris agreement. Even though hydrogen demand is expected to increase over the next years, the exact demand level over time remains a main source of uncertainty. We study the problem of where and when to locate hydrogen production plants to satisfy uncertain future customer demand. We formulate our problem as a two-stage stochastic multi-period facility location and capacity expansion problem. The first-stage decisions are related to the location and initial capacity of the production plants and have to be taken before customer demand is known. They involve selecting a modular capacity with a piecewise linear, convex short-term cost function for the chosen capacity level. In the second stage, decisions regarding capacity expansion and demand allocation are taken. Given the complexity of the formulation, we solve the problem using a Lagrangian decomposition heuristic. Our method is capable of finding solutions of sufficiently high quality within a few hours, even for instances too large for commercial solvers. We apply our model to a case from Norway and design the corresponding hydrogen infrastructure for the transportation sector.

Multi-input model uncertainty analysis for long-range wind farm noise predictions

One of the major sources of uncertainty in predictions of wind farm noise (WFN) reflect parametric and model structure uncertainty. The model structure uncertainty is a systematic uncertainty, which relates to uncertainty about the appropriate mathematical structure of the models. Here we quantified the model structure uncertainty in predicting WFN arising from multi-input models, including nine ground impedance and four wind speed profile models. We used a numerical ray tracing sound propagation model for predicting the noise level at different receivers. We found that variations between different ground impedance models and wind speed profile models were significant sources of uncertainty, and that these sources contributed to predicted noise level differences in excess of 10 dBA at distances greater than 3.5 km. We also found that differences between atmospheric vertical wind speed profile models were the main source of uncertainty in predicting WFN at long-range distances. When predicting WFN, it is important to acknowledge variability associated with different models as this contributes to the uncertainty of the predicted values.

Benchmarking Fast Neutrons Leakage Spectrum From Copper Block With 252Cf Source in Center

Abstract Copper is an important material for the nuclear industry; therefore, the correct copper cross section are essential. This paper deals with benchmarking the fast neutron leakage spectrum from a copper block with an intense 252Cf source. The spectrum was measured by the proton recoil method using a stilbene scintillator and spectrometer with pulse shape discrimination. The room effect was subtracted experimentally by shielding cone and confirmed computationally. Simulations were performed using the MCNP6.2 Monte Carlo code. A detailed study on uncertainties has been made. Consequently, as the main source of uncertainties, the measurement apparatus was determined (namely, calibration and number of iterations—up to 15%). From the parameter uncertainty, the most important effects are connected with the mass of cube material—the thickness of the assembly (up to 2%). The effect of copper density uncertainty is low because density was determined experimentally with low uncertainty. The uncertainty related to parameter uncertainties in source structural components is negligible because even neglection of all components leads to a shift in leakage spectra below 7%. Several copper nuclear data libraries were tested as well, and it was found that the calculation with JEFF-3.3 gives the most discrepant results with a discrepancy of up to 60%. The closest results were obtained with ENDF/B-VIII.0 (below 5 MeV, discrepancy within 10%) and JENDL-4.0 (above 5 MeV, discrepancy within 15%). ENDF/B-VII.1 library is relatively close in the region above 5 MeV (discrepancy within 15%), below 5 MeV the agreement is worse (up to 40% discrepancy).

Risk assessment of Citripestis sagittiferella for the EU.

Following a request from the European Commission, the EFSA Panel on Plant Health performed a risk assessment of Citripestis sagittiferella (Lepidoptera: Pyralidae), the citrus pulp borer, an oligophagous pest reported from South-East Asia and restricted to Citrus spp. The entry risk assessment focused on the citrus fruit pathway. Two scenarios were considered: scenario A0 (current practice) and A2 (additional post-harvest cold treatment). Based on the outputs of the entry model obtained in scenario A0, the median number of founder populations in the EU citrus-growing area is estimated to be slightly less than 10 per year (90%-uncertainty interval between about one entry per 180 years and 1,300 entries per year). The risk of entry and the simulated numbers of founder populations are orders of magnitude lower for scenario A2 compared to scenario A0. The key uncertainties in the entry model include transfer, the cold treatment effectiveness, the disaggregation factor and sorting. The simulated numbers of established populations are only slightly lower than the numbers of founder populations. As the probability of establishment has little impact on the number of established populations, it is not a major source of uncertainty, despite the lack of data on the thermal biology of the pest. The median lag period between establishment and spread is estimated to be slightly more than 1 year (90%-uncertainty interval between about 2months and 33months). After the lag period, the median spread rate by natural means (flying) and due to transport of harvested citrus fruit from orchards to packinghouses is estimated at about 100km/year (90%-uncertainty interval between about 40 and 500km/year). The main sources of uncertainties affecting the spread rate include the extent to which environmental factors could hamper the build-up of the populations and the lack of data on the spread rate at the origin. The median impact of C. sagittiferella in the EU citrus-growing area is estimated at about 10% of infested fruits among the harvested citrus fruits (90%-uncertainty interval between about 2% and 25%). Uncertainties affecting the impact assessment include the susceptibility of different Citrus species and cultivars.

Dynamic crack penetration vs. deflection at material interfaces and the role of rate dependent strength and toughness

This work presents a numerical investigation into the dynamic crack penetration vs. deflection at a material interface, for materials exhibiting strain rate dependent damage evolution. The rate dependence of damage manifests as an increased strength and fracture energy (or toughness) at higher strain rates. For this purpose, a strain rate dependent continuum damage mechanics (CDM) based model is considered, which scales the material point softening damage law as a function of the strain rate. The investigations consider two materials, viz. the bulk and the interface, both modeled via the foregoing rate dependent damage model. Attention is focused on a mode I dynamic bulk crack impinging the interface at right angles, for the case where the interface is more strain rate sensitive than the bulk. The model is calibrated and validated with experimental data, and found to predict well the penetration/deflection behavior of a dynamic crack at an interface. Despite this, the predicted crack trajectory approaching the specimen boundary appears to be affected in some cases. The model is then used to conduct a sensitivity analysis for a wide range of bulk and interface properties (moduli, strengths, and fracture energy). The analyses reveal that dynamic crack impingement at the interface is accompanied by sharp changes in the local strain rates, thus altering the local bulk and interface strengths and toughnesses. So, a weak interface can become stronger and tougher than the bulk, locally and instantaneously, if it exhibits a higher strain rate sensitivity than the bulk. This implies that when damage evolution is rate dependent, there is an increased tendency for crack penetration. Due to the local and instantaneous rate dependence of strength and toughness, the previously established criteria in terms of the quasistatic property ratios are shown to be inapplicable. Alternatively, modeling is deemed inevitable for which the main source of uncertainty comes from the boundary conditions, which are shown to significantly affect the predicted cracking behavior.

Global evaluation of model agreement and uncertainty in terrestrial water storage simulations from ISIMIP 2b framework

Terrestrial water storage (TWS) is a vital component in global hydrologic cycle with direct linkage to water resources availability and hydrologic extremes. Assessing the uncertainty in TWS projections are fundamentally important for developing counter-measures against impacts of climate change on water resources and disasters. This study presents a global-scale evaluation of model agreement and uncertainty in TWS anomaly (TWSA) simulations within the ISIMIP 2b framework by comparison with the 2006–2016 Gravity Recovery and Climate Experiment (GRACE) data. The total 24 members of ISIMIP2b ensembles considered here include the permutations of 6 global water models (GWMs: CLM4.5, H08, LPLmL, MATSIRO, PCR-GLOBWB, WaterGAP2) simulations forced by 4 global climate models (GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC5) under RCP2.6 and RCP6.0 scenarios. Results show that the fraction of global land area with the same sign between the ISIMIP2b ensemble mean and GRACE TWSA is 47.5 % and 47.3 % under RCP2.6 and RCP6.0, respectively. The ensemble mean reproduces the negative (positive) TWSA in southern North America, southwestern Asia, northern and central Africa (central South America and northern Europe) under both scenarios. More than 50 % of ensemble members agree with GRACE TWS better in the sign of drying trend than wetting trend over the global land. The interannual TWS variations among ensemble members show better agreement in North America and Europe than other continents. More than 80 % of ensemble members simulate larger (smaller) TWS seasonal amplitude than GRACE in North America, Europe, and Asia (South America, Africa, and Australia). GWM is found to be the main source of uncertainty in TWS simulations in North America, Europe, and Asia (>55 %), while GCM uncertainty is the dominant uncertainty source in South America, Africa, and Australia (>45 %).

ECG Measurement Uncertainty Based on Monte Carlo Approach: An Effective Analysis for a Successful Cardiac Health Monitoring System.

Measurement uncertainty is one of the widespread concepts applied in scientific works, particularly to estimate the accuracy of measurement results and to evaluate the conformity of products and processes. In this work, we propose a methodology to analyze the performance of measurement systems existing in the design phases, based on a probabilistic approach, by applying the Monte Carlo method (MCM). With this approach, it is feasible to identify the dominant contributing factors of imprecision in the evaluated system. In the design phase, this information can be used to identify where the most effective attention is required to improve the performance of equipment. This methodology was applied over a simulated electrocardiogram (ECG), for which a measurement uncertainty of the order of 3.54% of the measured value was estimated, with a confidence level of 95%. For this simulation, the ECG computational model was categorized into two modules: the preamplifier and the final stage. The outcomes of the analysis show that the preamplifier module had a greater influence on the measurement results over the final stage module, which indicates that interventions in the first module would promote more significant performance improvements in the system. Finally, it was identified that the main source of ECG measurement uncertainty is related to the measurand, focused towards the objective of better characterization of the metrological behavior of the measurements in the ECG.

Instant yield stress measurement from falling drop size: The “syringe test”

We analyze different flow regimes of a filament formed by extrusion of a material through a cylindrical die. We deduce that the elongational yield stress of a simple yield stress fluid (i.e., with negligible thixotropy effects) can be determined from the mass of the droplet after filament breakage and an estimation of the critical radius at pinch-off at the solid-liquid regime transition. We demonstrate that such a simple characterization is relevant in a relatively wide range of extrusion velocities, i.e., this velocity slightly affects the drop mass in this range. For the simple yield stress fluids used, Carbopol gel, clay-water paste at different concentrations, and emulsion, covering a large range of yield stress values (50–1000 Pa), the elongational yield stress appears to be equal to the simple shear yield stress times a factor equal to about 1.53. As a consequence, this simple test may be used to obtain, almost instantaneously and without sophisticated apparatus (a syringe and a balance are sufficient), a good estimate of the shear yield stress of simple yield stress fluids. In that case, the main source of uncertainty (up to about 20%) is the value of the critical radius at the solid-liquid transition. Finally, we review the operating conditions (material properties and extrusion characteristics) for which we can expect this approach to be valid.

The Effect of Probabilistic Window Opening Behavior of Occupants on Adaptive Thermal Comfort (The Case of Courtyard House in Yazd, Bandar Abbas, and Tabriz)

Considering the global energy crisis and the need to reduce energy consumption while providing thermal comfort to occupants, building performance prediction using building simulation programs requires higher accuracy of output data. Therefore, it seems necessary to study the impact of occupant behavior, which is the main source of uncertainty in residential buildings. The traditional courtyard houses, which are recognized as a successful passive house model, respond to different climatic conditions. Therefore, this research focuses on this building type to analyze occupant window opening control scenarios and determine which control works better. For this purpose, several probabilistic controls and their effects on the adaptive thermal comfort of occupants in zones around a central courtyard were compared in the three cities of Yazd, Bandar Abbas, and Tabriz. Energy Plus was used as a simulation program for the application of Grasshopper's energy management system (EMS) along with the Ladybug and Honeybee environmental plugins. The results show that the window control algorithms can increase the adaptive thermal comfort of occupants by 25.7%, 32.2%, and 20.3% in each of the climates of Yazd, Bandar Abbas, and Tabriz cities, respectively. Indoor and outdoor temperature were the most significant variables for opening windows in the warm and cold seasons, respectively.