Elasto-Plastic Response of Uniformly Loaded Sector Plates: Full-Section Yield Model Predictions and Spread of Plasticity

2009 ◽  
Author(s):  
G.J. Turvey ◽  
M. Salehi
Keyword(s):  
Plastic Response ◽  
Yield Model ◽  
Model Predictions ◽  
Section Yield

Improving growth and yield estimates with a process model derived growth index

2004 ◽  
Vol 34 (6) ◽  
pp. 1274-1282 ◽  
Author(s):  
Jason G Henning ◽  
Thomas E Burk
Keyword(s):  
Process Model ◽  
Environmental Variability ◽  
Growth Index ◽  
Process Models ◽  
Growth And Yield ◽  
Yield Model ◽  
Forest Inventories ◽  
Model Predictions ◽  
Growth And Yield Models ◽  
Empirical Growth

Forest managers have long made use of the regular and predictable nature of tree growth by using empirical growth and yield models to update forest inventories. Updated inventories support better decision making without requiring on the ground reassessment of the forest resource. Growth and yield model predictions can suffer from inaccuracies due to the influence of climate and environmental variability on the growth of trees. Researchers have been attempting to assess and predict the effect of this variation by developing mechanistic process models that often do not generate outputs applicable to inventory update. Here we create a growth index dependent on process model outputs to improve growth and yield estimates. Estimate accuracy was modestly improved over the basic growth and yield estimates and was comparable to previous efforts to account for environmental variability in growth and yield estimates. Using a process model we are nominally considering the entire environment, and by adjusting the growth and yield estimates external to both model types we have avoided difficulties involved with refitting or recreating either model. These are key differences from previous efforts to include environmental variability in growth and yield estimates.

Application of the Strip Yield Model to Crack Growth Predictions for Structural Steel

2010 ◽  
Vol 57 (1) ◽  
pp. 1-20
Author(s):  
Małgorzata Skorupa ◽  
Tomasz Machniewicz
Keyword(s):  
Structural Steel ◽  
Crack Growth ◽  
Model Calibration ◽  
Load History ◽  
Yield Model ◽  
Variable Amplitude Loading ◽  
Variable Amplitude ◽  
Constraint Factors ◽  
Strip Yield Model ◽  
Closure Mechanism

Application of the Strip Yield Model to Crack Growth Predictions for Structural SteelA strip yield model implementation by the present authors is applied to predict fatigue crack growth observed in structural steel specimens under various constant and variable amplitude loading conditions. Attention is paid to the model calibration using the constraint factors in view of the dependence of both the crack closure mechanism and the material stress-strain response on the load history. Prediction capabilities of the model are considered in the context of the incompatibility between the crack growth resistance for constant and variable amplitude loading.

ESTIMASI HASIL AIR DARI DAERAH TANGKAPAN AIR DANAU RAWA PENING DENGAN MENGGUNAKAN MODEL INVEST

2017 ◽  
Vol 19 (2) ◽  
pp. 157
Author(s):  
Nunung Puji Nugroho
Keyword(s):  
Spatial Distribution ◽  
Ecosystem Services ◽  
Water Resources ◽  
High Water ◽  
Water Yield ◽  
Accurate Information ◽  
Yield Model ◽  
Catchment Areas ◽  
Integrated Valuation ◽  
Valuation Of Ecosystem Services

<p class="JudulABSInd"><strong>ABSTRAK</strong></p><p class="abstrak">Informasi hasil air dari suatu ekosistem sangat penting dalam pengelolaan sumber daya air. Dalam perencanaan kegiatan konservasi sumber daya air, informasi sebaran spasial hasil air diperlukan untuk menentukan prioritas wilayah terkait dengan alokasi anggaran. Hasil air dari suatu ekosistem atau daerah aliran sungai (DAS) dapat diestimasi dengan menggunakan model hidrologi. Penelitian ini bertujuan untuk mendapatkan informasi tentang hasil air, baik besaran maupun sebaran spasialnya, dari daerah tangkapan air (DTA) Danau Rawa Pening. Hasil air dari lokasi penelitian dihitung dengan menggunakan model hasil air pada InVEST (<em>the Integrated Valuation of Ecosystem Services and Tradeoffs</em>), yang didasarkan pada pendekatan neraca air. Hasil perhitungan menunjukkan bahwa volume hasil air di DTA Danau Rawa Pening pada tahun 2015 adalah sekitar 337 juta m<sup>3</sup>. SubDAS Galeh, sebagai subDAS terluas, merupakan penghasil air terbesar (72,4 juta m<sup>3</sup>) diikuti oleh subDAS Sraten (66,8 juta m<sup>3</sup>) dan Parat (62,4 juta m<sup>3</sup>). Secara spasial, hasil air di lokasi kajian mempunyai nilai antara 0 hingga 29.634,19 m<sup>3</sup>/ha. Wilayah hulu dan tengah subDAS Sraten secara umum mempunyai hasil air yang lebih tinggi, sedangkan wilayah danau dan sekitarnya serta hulu subDAS Galeh mempunyai hasil air yang lebih rendah dibandingkan dengan wilayah lainnya. Wilayah dengan hasil air tinggi dapat diprioritaskan dalam kegiatan konservasi sumber daya air untuk mendukung pasokan air ke Danau Rawa Pening.</p><p><strong><em>Kata kunci</em></strong><em>: hasil air, daerah tangkapan air, model InVEST, Danau Rawa Pening</em><em></em></p><p class="judulABS"><strong>ABSTRACT</strong></p><p class="Abstrakeng">Accurate information on water yield from an ecosystem is very important in the management of water resources. In the planning of water resources conservation activities, the information on the spatial distribution of water yield is needed to determine regional priorities related to budget allocations. The water yield from an ecosystem or watershed can be estimated using a hydrological model. This study aimed to obtain information about the water yield, both the magnitude and their spatial distribution, from the catchment areas of Lake Rawa Pening. The water yield from the study area was calculated using the water yield model in InVEST (the Integrated Valuation of Ecosystem Services and Tradeoffs), which based on the water balance approach. The results indicated that the volume of water yield in Lake Rawa Pening for 2015 is approximately 337 million m<sup>3</sup>. Galeh subwatershed, as the largest subwatershed, is the largest water producer (72.4 million m<sup>3</sup>), followed by Sraten subwatershed (66.8 million m<sup>3</sup>) and Parat subwatershed (62.4 million m<sup>3</sup>). Spatially, the water yield at the study site has a value between 0 to 29,634.19 m<sup>3</sup>/ha. Upstream and middle areas of Sraten subwatershed generally have higher water yield, while the lake and its surrounding areas as well as the upstream of Galeh subwatershed have lower water yield compared to other regions. The regions with high water yield can be prioritized in water resource conservation activities to support the supply of water to Lake Rawa Pening.</p><p><strong><em>Keywords</em></strong><em>: water yield, catchment areas, InVEST model, Lake Rawa Pening</em><em></em></p>

Sign in / Sign up

Export Citation Format

Share Document