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Thematische Bibliographien / Moisture

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Auswahl der wissenschaftlichen Literatur zum Thema „Moisture“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 29. Juli 2024

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Zeitschriftenartikel zum Thema "Moisture"

1

Hatton, Thomas J., Neil R. Viney, E. A. Catchpole und Neville J. De Mestre. „The Influence of Soil Moisture on Eucalyptus Leaf Litter Moisture“. Forest Science 34, Nr. 2 (01.06.1988): 292–301. http://dx.doi.org/10.1093/forestscience/34.2.292.

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Abstract An experiment was carried out to test the assumption that surface soil moisture affects fine dead fuel moisture. A randomized block design was used to test the response in Eucalyptus leaf moisture to two levels of soil moisture over a range of exposures to the sun, wind, and soil surface. Soil moisture clearly influenced daily leaf fuel moisture minima and maxima. The effect on daily minima was most pronounced for the bottom of the litter layer, which was shielded from the sun and wind and in contact with the soil. The effect of soil moisture on daily fuel moisture maxima was most pronounced for exposed samples. The responses in fuel moisture due to exposure and soil moisture were compared with fine fuel moistures predicted by three fuel moisture models. The various treatment combinations of soil moisture and exposure produced fuel moistures that varied too widely for any of the tested fuel moisture models to be consistently most accurate. For. Sci. 34(2):292-301.

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Gumma, Miss Rachana, Miss Rutuja Magar und Miss Anuradha Dhavan Prof Jagtap S. C. „Development of Grain Moisture meter with Moisture and Price Display“. International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (30.04.2018): 2023–25. http://dx.doi.org/10.31142/ijtsrd11587.

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3

Egger, Joseph. „The moisture torque“. Meteorologische Zeitschrift 15, Nr. 6 (20.12.2006): 671–73. http://dx.doi.org/10.1127/0941-2948/2006/0131.

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4

Li, Xin, Yudong Lu, Xiaozhou Zhang, Rong Zhang, Wen Fan und Wangsheng Pan. „Influencing Factors of the Spatial–Temporal Variation of Layered Soils and Sediments Moistures and Infiltration Characteristics under Irrigation in a Desert Oasis by Deterministic Spatial Interpolation Methods“. Water 11, Nr. 7 (17.07.2019): 1483. http://dx.doi.org/10.3390/w11071483.

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Soil moisture is the main limiting factor for crop growth and the sustainable development of oases in arid desert areas. Therefore, the temporal and spatial variation and infiltration laws of oasis soil moisture should be studied. The objective of this study is to reveal the influencing factors of the spatial–temporal variation of layered soil and sediment moisture and infiltration characteristics under irrigation in desert oases. Hydraulic conductivities were measured using the double-ring infiltrometer, while the regional and site soil moistures were measured and calibrated using weighted method and neutron moisture meter. Deterministic spatial interpolation methods, including multiquadric radial basis function, inverse distance weighted, and local polynomial regression isogram, were adopted to map the regional distribution of hydraulic conductivities, spatial soil moistures, and spatial–temporal isogram of the point site soil moistures in Yaoba Oasis, respectively. Results showed that the leading influencing factors of the (1) regional spatial soil moisture were soil and sediment permeability, stream link direction, microclimate, and dewfalls; (2) spatial layered soil and sediment moistures were microclimate and dew condensation; and (3) spatial–temporal variation at the point site profiles were soil texture, water requirement, and preferential flow. Under irrigation, soil moisture increased significantly, in which the maximum increase was 10.8 times the original state, while the recharging depth substantially increased up to 580 cm with the preferential flow. The spatial–temporal variation of the soil moisture under irrigation indicated that the best irrigation frequency should be 15 days per time. Moreover, the infiltration process can be divided into the preferential flow, piston flow, and balanced infiltration stages.

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Yang, Kun, Toshio Koike, Ichirow Kaihotsu und Jun Qin. „Validation of a Dual-Pass Microwave Land Data Assimilation System for Estimating Surface Soil Moisture in Semiarid Regions“. Journal of Hydrometeorology 10, Nr. 3 (01.06.2009): 780–93. http://dx.doi.org/10.1175/2008jhm1065.1.

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Abstract This study examines the capability of a new microwave land data assimilation system (LDAS) for estimating soil moisture in semiarid regions, where soil moisture is very heterogeneous. This system assimilates the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) 6.9- and 18.7-GHz brightness temperatures into a land surface model (LSM), with a radiative transfer model as an observation operator. To reduce errors caused by uncertainties of system parameters, the LDAS uses a dual-pass assimilation algorithm, with a calibration pass to estimate major model parameters from satellite data and an assimilation pass to estimate the near-surface soil moisture. Validation data of soil moisture were collected in a Mongolian semiarid region. Results show that (i) the LDAS-estimated soil moistures are comparable to areal averages of in situ measurements, though the measured soil moistures were highly variable from site to site; (ii) the LSM-simulated soil moistures show less biases when the LSM uses LDAS-calibrated parameter values instead of default parameter values, indicating that the satellite-based calibration does contribute to soil moisture estimations; and (iii) compared to the LSM, the LDAS produces more robust and reliable soil moisture when forcing data become worse. The lower sensitivity of the LDAS output to precipitation is particularly encouraging for applying this system to regions where precipitation data are prone to errors.

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Sakvarelidze, Amiran. „Determining Basalt Fiber Concrete Moisture Conductivity Characteristics“. Works of Georgian Technical University, Nr. 3(529) (27.09.2023): 115–22. http://dx.doi.org/10.36073/1512-0996-2023-3-115-122.

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Issues concerning cement-based composites basalt fiber concrete’s moisture conductivity are studied in the article. Composites moisture conductivity parameters (moisture diffusion, moisture transfer and relative moisture transfer coefficients) are identified by drying testing on specimens. Experiments are conducted by testing specimens of ( 0t 28 = day age) and containing moisture of ( W 4.5% 0 = according to mass) on drying. Specimens were dried up in the environment of 20% relative humidity. Drying process duration was (190 days) till the equilibrium moister content was met, when moisture transfer (drying) between environment and specimen stops, W 1% C = (according to mass). During drying process moisture loss in specimens were identified with periodic weighing. Cylindrical specimens (with isolated endings) were experiencing drying process from free lateral surfaces. Weight experiment data analyses determined curve of basal fiber concrete moister content changes in time. Parallel to tests cylinders moisture content change was calculated theoretically at any point in time for χ - coefficient’s different values. N number of theoretical curves is received. By comparing and analyzing experimental and theoretical data such a value of χ - coefficient is chosen that can ensure that theoretical curve can reflect experimental curve as much as possible. On the bases of a given data with corresponding formulas moisture conductivity characteristics of basalt fiber concrete: (moisture diffusion, moisture transfer and relative moisture transfer) values are determined.

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Mirzasharifovna, Kipchakova Gavharay. „THREE-WAVE MOISTURE METER“. International Journal of Advance Scientific Research 02, Nr. 12 (01.12.2022): 73–78. http://dx.doi.org/10.37547/ijasr-02-12-11.

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Synchronous detectors are controlled by pulses from the corresponding power generator and, therefore, a signal is allocated that is proportional to the reflected radiation flux at the corresponding wavelength, which is then fed to the input of the information processing unit.

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Watwood, Mary E., John W. Fitzgerald und Wayne T. Swank. „Effects of moisture content on sulfate generation and retention in hardwood forest upper soil horizons“. Canadian Journal of Forest Research 18, Nr. 6 (01.06.1988): 823–27. http://dx.doi.org/10.1139/x88-126.

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The influence of moisture on organic S mineralization and the fate of both mineralization-derived and added sulfate were examined in A and B horizon soil samples from a hardwood forest. The sulfur-containing amino acid methionine was chosen to study organic S mineralization. 35S-labelled sulfate or methionine was added to field-moist samples, which were then suction dried to contain between 2 and 80% moisture. Both added sulfate-S and sulfate-S released by methionine mineralization was incorporated into organic matter, and the highest levels of organic S formed were observed for those A and B horizon samples containing between 25 and 35% moisture. The A horizon incorporated much less added sulfate under very dry than under extremely moist conditions. The B horizon exhibited substantial decreases under both extreme moisture regimes. At moisture contents over 30%, high levels of methionine mineralization were observed, and at lower moisture contents mineralization decreased substantially. For soil moistures lower than 10 and 20% for the A and B horizons, respectively, most of the added methionine remained nonmineralized following incubation. In addition to mineralization, a portion of the added methionine was also incorporated directly into organic matter. The highest levels of this incorporation were achieved at soil moistures between 20 and 35%.

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Chrosciewicz, Z. „Prediction of forest-floor moisture content on jack pine cutovers“. Canadian Journal of Forest Research 19, Nr. 2 (01.02.1989): 239–43. http://dx.doi.org/10.1139/x89-033.

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Moisture contents of organic forest-floor materials were studied by strata on a clear-cut jack pine (Pinusbanksiana Lamb.) site in relation to slash distribution and changes in both duff moisture code and fine fuel moisture code, the two weather-based components of the Canadian Forest Fire Weather Index System. The best-fitting curvilinear regression (Y = a + b/X) of the duff moisture code showed distinctive patterns of variation, so that both the surface and subsurface forest-floor strata were consistently moister under slash cover than in slash openings, and for each of these two slash conditions, the subsurface forest-floor strata were consistently moister than the surface strata. Combinations of these materials down to mineral soil showed intermediate moisture contents both in slash openings and under slash cover. The straight line regression (Y = a + bX) of the fine fuel moisture code was the best-fitting moisture content relationship for the surface forest-floor materials, but only in slash openings; under slash cover, the curvilinear regression (Y = a + b/X) of the duff moisture code was more suitable. The coefficients of correlation, r, as derived from these varied regressions, were all very highly significant at P < 0.001.

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Hervai, András, Ervin Pirkhoffer, Szabolcs Ákos Fábián, Ákos Halmai, Gábor Nagy, Dénes Lóczy und Szabolcs Czigány. „Interpolation and 3D visualization of soil moisture“. Landscape & Environment 11, Nr. 1 (31.12.2017): 23–34. http://dx.doi.org/10.21120/le/11/1/3.

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Adaptation to climate change demands the optimal and sustainable water management in agriculture, with an inevitable focus on soil moisture conditions. In the current study we developed an ArcGIS 10.4. platform-based application (software) to model spatial and temporal changes in soil moisture in a soy field. Six SENTEK Drill & Drop soil moisture sensors were deployed in an experimental field of 4.3 hectares by the contribution of Elcom Ltd. Soil moisture measurement at each location were taken at six depths (5, 15, 25, 35, 45 and 55 cm) in 60-minute intervals. The model is capable to spatially interpolate monitored soil moisture using the technique. The time sequence change of soil moistures can be tracked by a Time Slider for both the 2D and 3D visualization. Soil moisture temporal changes can be visualized in either daily or hourly time intervals, and can be shown as a motion figure. Horizon average, maximum and minimum values of soil moisture data can be identified with the builtin tool of ArcGIS. Soil moisture spatial distribution can be obtained and plotted at any cross sections, whereas an alarm function has also been developed for tension values of 250, 1,000 and 1,500 kPa.

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Dissertationen zum Thema "Moisture"

1

Mwesigwa, Enosh. „Permeation of moisture through moisture barrier coatings“. Thesis, University College London (University of London), 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.435802.

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Kankanala, Sujitha. „Advanced Moisture Control : Moisture measurement in textiles“. Thesis, Linnéuniversitetet, Institutionen för fysik och elektroteknik (IFE), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-97939.

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Waichungo, Wamwarī W. „Textural characteristics of low moisture-crisp foods during moisture sorption and storage /“. free to MU campus, to others for purchase, 1996. http://wwwlib.umi.com/cr/mo/fullcit?p9823333.

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Sherratt, David Joseph. „Regional soil moisture modelling“. Thesis, Imperial College London, 1985. http://hdl.handle.net/10044/1/8230.

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He, Xiao. „Moisture sorption and gas emissions during the storage of high moisture woody biomass“. Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/44228.

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Moisture sorption and gas emissions are major processes associated with biomass storage. Depending on the storage conditions, these processes alter the structure and composition of biomass. The objectives of this research are (1) to develop moisture relations for woody biomass exposed to drying and wetting environments; (2) to quantify gas emissions from biomass stored under aerobic and anaerobic conditions; and (3) to develop dry matter loss equations for the stored biomass. Moisture adsorption and desorption (drying) experiments were carried out on Aspen branches in a controlled temperature and humidity chamber. Frequent wetting-drying cycles were simulated by spraying water on the biomass. A lump model for simulating moisture adsorption-desorption was developed and calibrated with experimental results. The model was applied to the Aspen bales stored for one year in the field under natural conditions. The predicted moisture contents using the lump moisture transfer model were found to be in reasonably good agreement with the moisture contents measured in the stored bales. In another set of experiments, gas emissions from stored Western Red Cedar (WRC) and Douglas fir (DF) were analyzed. The emissions of CO₂, CO, H₂ and CH₄, and the depletion of O₂ were measured. The highest total CO₂ emissions from WRC stored in the non-aerobic and aerobic reactors were 2.8 g/kg DM and 6.6 g/kg DM, respectively. Higher gas emissions were measured from stored DF materials than from WRC. Common volatile organic compounds (VOCs) measured using GC-MS were methanol, aldehydes, terpene, acid, acetone, hexane, ketone, benzene, ethers and esters from WRC and DF. The total VOC concentrations were found to have a positive correlation with temperature. The results of microbial analysis were compatible with gas emission results. Positive correlations between percent dry matter losses and gas emissions were found for both aerobic and non-aerobic storage conditions. The summation of gas emissions from aerobic reactors is greater than accumulated gas emissions from non-aerobic reactors over the same storage period. It was found that DF is more readily degradable than WRC. Greens (leaves and twigs) degrade faster than wood chips.

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Omotere, Olumide Olubunmi. „Improvement of the Soil Moisture Diagnostic Equation for Estimating Root-Zone Soil Moisture“. Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1157607/.

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Soil moisture information can be used accurately in determining the timing and amount of irrigation applied to plants. Pan and Pan et al. proposed a robust and simple daily diagnostic equation for estimating daily soil moisture. The diagnostic equation evaluates the relationship between the soil moisture loss function and the summation weighted average of precipitation. The loss function uses the sinusoidal wave function which employs day of the year (DOY) to evaluate the seasonal variation in soil moisture loss for a given year. This was incorporated into the daily diagnostic equation to estimate the daily soil moisture for a location. Solar radiation is an energy source that drives the energy and water exchanges between vegetation and the atmosphere (i.e., evapotranspiration), and thus impacts the soil moisture dry-down. In this paper, two parameters (the actual solar radiation and the clear sky solar radiation) are introduced into loss function coefficient to improve the estimation of soil moisture. After the Introduction of the solar radiation data into soil moisture loss function, a slight improvement was observed in the estimated daily soil moisture. Pan observed that generally the correlation coefficient between the estimated and the observed soil moisture is above 0.75 and the root mean square error is below 5.0 (%v/v). The introduction solar radiation data (i.e. clear sky solar radiation and actual solar) improve the correlation coefficient average for all the sites evaluated by 0.03 when the root mean square error is generally below 4.5(%v/v) for the entire root zone.

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Soriano, Melissa. „Estimation of soil moisture in the southern united states in 2003 using multi-satellite remote sensing measurements“. Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3361.

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Thesis (M.S.)--George Mason University, 2008.
Vita: p. 65. Thesis director: John Qu. Submitted in partial fulfillment of the requirements for the degree of Master of Science in Earth System Science. Title from PDF t.p. (viewed Jan. 11, 2009). Includes bibliographical references (p. 59-64). Also issued in print.

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Eakes, Donald Joseph. „Moisture stress conditioning, potassium nutrition, and tolerance of Salvia splendens 'Bonfire' to moisture stress“. Diss., Virginia Polytechnic Institute and State University, 1989. http://hdl.handle.net/10919/54350.

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The objective of this study was to determine the leaf water relations, gas exchange, and growth of the bedding plant salvia Salvia splendens 'Bonfire‘ as influenced by moisture stress conditioning (MSC - exposing plants to 4 sublethal dry-down cycles) and potassium (K) nutrition. Plants were fertilized with one of six K rates: 25, 75, 150, 300, 450, and 600 ppm as KCl in experiment one. Seven weeks after seeding plants were subjected to MSC. MSC and increasing K rate resulted in osmotic adjustment and increased cellular turgor potentials. Foliar K content increased as osmotic potentials decreased due to treatment. Although there was no interaction, MSC and high K rates both reduced transpiration (E), leaf conductance (g₁), and daily gravimetric water loss during well watered conditions. Greatest shoot dry weight occurred for plants grown with 300 ppm K and no-MSC. Gas exchange of salvia as influenced by MSC during the onset of moisture stress was determined in experiment two. On day one following final irrigation, MSC plants had lower mid-day E, g₁, hourly gravimetric water loss per unit leaf area, and net photosynthesis (Pn) compared to controls, despite no differences in leaf water potential (ψ₁). Percentage of stomatal inhibition of Pn (SI) was greater for MSC plants than controls with no differences in mesophyllic resistance to CO₂ (r_m). On day two, MSC plants had greater Pn, E, g₁, and hourly gravimetric water loss per unit leaf area, while SI and r_m were lower than controls. MSC plants maintained positive Pn rates and turgor to lower ψ₁ than control plants. Water use efficiency (WUE) estimates for MSC plants were greater than for controls. Salvia plants were fertilized with 75, 300, or 600 ppm K to determine the influence of K rate on gas exchange during the onset of moisture stress in a third experiment. On day one following final irrigation, plants grown with K rates of 300 and 600 ppm had lower E, g₁, hourly gravimetric water loss per unit leaf area, and Pn compared to 75 ppm K plants. On day two, 600 ppm K plants had greater Pn, E, and g₁ as the experiment was terminated compared to plants grown with 75 ppm K, although ψ₁ was similar. Potassium rate had little affect on WUE.
Ph. D.

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Donahoe, Daniel Noel. „Moisture in multilayer ceramic capacitors“. College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2189.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2005.
Thesis research directed by: Mechanical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Peralta, Perry Nacnac. „Nonisothermal moisture transport in wood“. Diss., This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-09192008-063154/.

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Bücher zum Thema "Moisture"

1

Stanwood, Phillip C., und Miller B. McDonald, Hrsg. Seed Moisture. Madison, WI, USA: Crop Science Society of America, 1989. http://dx.doi.org/10.2135/cssaspecpub14.

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United States. Federal Grain Inspection Service. Moisture handbook. [Washington, D.C.?]: U.S. Dept. of Agriculture, Federal Grain Inspection Service, 1986.

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Akre, Roger D. Moisture ants. [Pullman, Wash.]: Washington State University Cooperative Extension, 1998.

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Antonelli, Arthur L. Moisture ants. 2. Aufl. [Pullman, Wash.]: Washington State University Extension, 2003.

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Canada, Canada Natural Resources, Hrsg. Moisture problems. [Ottawa]: Natural Resources Canada, 1996.

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Antonelli, Arthur L. Moisture ants. 2. Aufl. [Pullman, Wash.]: Washington State University Extension, 2007.

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Ontario. Ministry of Agriculture and Food. High Moisture Corn. S.l: s.n, 1985.

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Timber Research and Development Association. Moisture in timber. High Wycombe: Timber Research and Development Association, 1991.

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Brook, David M. Home moisture problems. [Corvallis, Or.]: Oregon State University Extension Service, 1994.

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Association, Paper IndustryTechnical, Hrsg. Moisture profile correction. Bury: Paper Industry Technical Association, 1995.

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Buchteile zum Thema "Moisture"

1

Bährle-Rapp, Marina. „moisture“. In Springer Lexikon Kosmetik und Körperpflege, 359. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71095-0_6670.

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Crowe, John H., Lois M. Crowe, Folkert A. Hoekstra und Christina Aurell Wistrom. „Effects of Water on the Stability of Phospholipid Bilayers: The Problem of Imbibition Damage in Dry Organisms“. In Seed Moisture, 1–14. Madison, WI, USA: Crop Science Society of America, 2015. http://dx.doi.org/10.2135/cssaspecpub14.c1.

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Chin, H. F., B. Krishnapillay und P. C. Stanwood. „Seed Moisture: Recalcitrant vs. Orthodox Seeds“. In Seed Moisture, 15–22. Madison, WI, USA: Crop Science Society of America, 2015. http://dx.doi.org/10.2135/cssaspecpub14.c2.

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Kermode, Allison R., Maurice Y. Oishi und J. Derek Bewley. „Regulatory Roles for Desiccation and Abscisic Acid in Seed Development: A Comparison of the Evidence from Whole Seeds and Isolated Embryos“. In Seed Moisture, 23–50. Madison, WI, USA: Crop Science Society of America, 2015. http://dx.doi.org/10.2135/cssaspecpub14.c3.

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Leopold, A. Carl, und Christina W. Vertucci. „Moisture as a Regulator of Physiological Reaction in Seeds“. In Seed Moisture, 51–67. Madison, WI, USA: Crop Science Society of America, 2015. http://dx.doi.org/10.2135/cssaspecpub14.c4.

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Grabe, D. F. „Measurement of Seed Moisture“. In Seed Moisture, 69–92. Madison, WI, USA: Crop Science Society of America, 2015. http://dx.doi.org/10.2135/cssaspecpub14.c5.

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Vertucci, Christina W. „The Kinetics of Seed Imbibition: Controlling Factors and Relevance to Seedling Vigor“. In Seed Moisture, 93–115. Madison, WI, USA: Crop Science Society of America, 2015. http://dx.doi.org/10.2135/cssaspecpub14.c6.

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Spiridonov, Vlado, und Mladjen Curic. „Atmospheric Moisture“. In Fundamentals of Meteorology, 123–33. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52655-9_10.

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Kolev, Nikolay Ivanov. „Moisture Separation“. In Multiphase Flow Dynamics 5, 363–450. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15156-4_9.

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Engman, E. T., und R. J. Gurney. „Soil moisture“. In Remote Sensing in Hydrology, 127–54. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-009-0407-1_7.

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Konferenzberichte zum Thema "Moisture"

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Aree-Uea, A., A. Mavinkurve, M. van Soestbergen und R. T. H. Rongen. „Accelerated Moisture Soak for Moisture Sensitivity Analysis Revisited“. In 2018 IEEE 20th Electronics Packaging Technology Conference (EPTC). IEEE, 2018. http://dx.doi.org/10.1109/eptc.2018.8654307.

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Hatanaka, Daisuke, Alireza Ahrary und Dennis Ludena. „Research on Soil Moisture Measurement Using Moisture Sensor“. In 2015 IIAI 4th International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2015. http://dx.doi.org/10.1109/iiai-aai.2015.289.

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Hao-cheng, He, Li Shao-ming, Liu Zhe, Wang Hu, An Dong, Zhang Xiao-dong, Zhu De-hai und Bai Chang-qing. „Error Analysis of High-moisture Maize Moisture Measurement with PM-8188 Grain Moisture Tester“. In 2011 First International Conference on Instrumentation, Measurement, Computer, Communication and Control (IMCCC). IEEE, 2011. http://dx.doi.org/10.1109/imccc.2011.9.

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4

Sasi, Arun, und Przemyslaw Gromala. „Simulating moisture diffusion in polymers using thermal-moisture analogy“. In 2016 17th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE). IEEE, 2016. http://dx.doi.org/10.1109/eurosime.2016.7463372.

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5

Bastholm, Camilla, Jens Frisvad, Anne Mette Madsen und Jane Richter. „What defines "Moisture in Buildings"?“ In 1st International Conference on Moisture in Buildings 2021. ScienceOpen, 2021. http://dx.doi.org/10.14293/icmb210007.

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6

Künzel, Hartwig. „How moisture control standards should be updated to improve moisture tolerance and practical applicability“. In 1st International Conference on Moisture in Buildings 2021. ScienceOpen, 2021. http://dx.doi.org/10.14293/icmb210035.

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7

Voss, E., M. Riebesell, W. Lahmann, C. Weitkamp und W. Michaelis. „Moisture Height Profiler“. In Hague International Symposium, herausgegeben von Hanspeter Lutz und Georges Otrio. SPIE, 1987. http://dx.doi.org/10.1117/12.941522.

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8

Jang, Changsoo, Bongtae Han, Seungbae Park und Samson Yoon. „Advanced Thermal-Moisture Analogy Scheme for Anisothermal Moisture Diffusion Problem“. In ASME 2007 InterPACK Conference collocated with the ASME/JSME 2007 Thermal Engineering Heat Transfer Summer Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/ipack2007-33142.

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Annotation:

We propose an advanced thermal-moisture analogy scheme to cope with the inherent limitations of the existing schemes. The new scheme is based on the experimentally-observed unique hygroscopic behavior of polymeric materials used in microelectronics; i.e., the saturated concentration is only a function of relative humidity regardless of temperature. A new analogy formulation based on the modified solubility is presented and the scheme is implemented to investigate its accuracy and applicability. The results from a simple case study corroborate that the advanced scheme can be used effectively for package assemblies subjected to general anisothermal loading conditions.

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9

Kočí, Václav, Jan Kočí, Kamil Ďurana, Jiří Maděra und Robert Černý. „Determination of moisture-dependent moisture diffusivity using smoothed experimental data“. In 11TH INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2013: ICNAAM 2013. AIP, 2013. http://dx.doi.org/10.1063/1.4825936.

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10

Carmeliet, Jan. „Multiscale unveil of moisture in buildings“. In 1st International Conference on Moisture in Buildings 2021. ScienceOpen, 2021. http://dx.doi.org/10.14293/icmb210015.

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Berichte der Organisationen zum Thema "Moisture"

1

DeJong, Joel, und Paul Kassel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2016. http://dx.doi.org/10.31274/farmprogressreports-180814-1372.

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2

DeJong, Joel, und Paul Kassel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2016. http://dx.doi.org/10.31274/farmprogressreports-180814-1401.

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3

DeJong, Joel L. Soil Moisture. Ames: Iowa State University, Digital Repository, 2010. http://dx.doi.org/10.31274/farmprogressreports-180814-152.

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4

DeJong, Joel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/farmprogressreports-180814-1690.

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5

DeJong, Joel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/farmprogressreports-180814-1721.

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6

DeJong, Joel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2018. http://dx.doi.org/10.31274/farmprogressreports-180814-1965.

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7

DeJong, Joel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2018. http://dx.doi.org/10.31274/farmprogressreports-180814-1977.

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8

DeJong, Joel L., und Paul C. Kassel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2007. http://dx.doi.org/10.31274/farmprogressreports-180814-2340.

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9

DeJong, Joel L., und Paul C. Kassel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2004. http://dx.doi.org/10.31274/farmprogressreports-180814-2398.

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10

DeJong, Joel L., und Paul C. Kassel. Soil Moisture. Ames: Iowa State University, Digital Repository, 2006. http://dx.doi.org/10.31274/farmprogressreports-180814-2502.

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