Large scale optimization of a sour water stripping plant using surrogate models

In this work, we propose a new methodology for the large scale optimization and process integration of complex chemical processes that have been simulated using modular chemical process simulators. Units with significant numerical noise or large CPU times are substituted by surrogate models based on Kriging interpolation. Using a degree of freedom analysis, some of those units can be aggregated into a single unit to reduce the complexity of the resulting model. As a result, we solve a hybrid simulation-optimization model formed by units in the original flowsheet, Kriging models, and explicit equations. We present a case study of the optimization of a sour water stripping plant in which we simultaneously consider economics, heat integration and environmental impact using the ReCiPe indicator, which incorporates the recent advances made in Life Cycle Assessment (LCA). The optimization strategy guarantees the convergence to a local optimum inside the tolerance of the numerical noise.

Penobscot County, Maine, 1859 (Image 1 of 2) (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Topographical map of the county of Penobscot Maine, from surveys under the direction of H.F. Walling; field work under the direction of L.H. Eaton. It was published by Lee & Marsh in 1859, Scale 1:80,000. This layer is image 1 of 2 total images, representing the southwest portion of the four sheet source map. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Universal Transverse Mercator projection (UTM Zone 19N, meters, NAD1983). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as roads, railroads, drainage, public buildings, schools, churches, cemeteries, industry locations (e.g. mills, factories, mines, etc.), private buildings with names of property owners, town boundaries, and more. Relief shown by hachures. It includes many cadastral insets of individual county towns and villages. It also includes illustrations, business directories, and tables of statistics and distances.This layer is part of a selection of digitally scanned and georeferenced historic maps of New England from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of regions, originators, ground condition dates, scales, and map purposes.

Penobscot County, Maine, 1859 (Image 2 of 2) (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Topographical map of the county of Penobscot Maine, from surveys under the direction of H.F. Walling; field work under the direction of L.H. Eaton. It was published by Lee & Marsh in 1859, Scale 1:80,000. This layer is image 2 of 2 total images, representing the northeast portion of the four sheet source map. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Universal Transverse Mercator projection (UTM Zone 19N, meters, NAD1983). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as roads, railroads, drainage, public buildings, schools, churches, cemeteries, industry locations (e.g. mills, factories, mines, etc.), private buildings with names of property owners, town boundaries, and more. Relief shown by hachures. It includes many cadastral insets of individual county towns and villages. It also includes illustrations, business directories, and tables of statistics and distances.This layer is part of a selection of digitally scanned and georeferenced historic maps of New England from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of regions, originators, ground condition dates, scales, and map purposes.

Interpolação projetual : explorando o espaço de possibilidades entre a menor complexidade e o maior desempenho

Tese de doutoramento, Belas-Artes (Design de Equipamento), Universidade de Lisboa, Faculdade de Belas-Artes, 2016

MOREMATA: Stata module (Mata) to provide various functions

This package includes various Mata functions. kern(): various kernel functions; kint(): kernel integral functions; kdel0(): canonical bandwidth of kernel; quantile(): quantile function; median(): median; iqrange(): inter-quartile range; ecdf(): cumulative distribution function; relrank(): grade transformation; ranks(): ranks/cumulative frequencies; freq(): compute frequency counts; histogram(): produce histogram data; mgof(): multinomial goodness-of-fit tests; collapse(): summary statistics by subgroups; _collapse(): summary statistics by subgroups; gini(): Gini coefficient; sample(): draw random sample; srswr(): SRS with replacement; srswor(): SRS without replacement; upswr(): UPS with replacement; upswor(): UPS without replacement; bs(): bootstrap estimation; bs2(): bootstrap estimation; bs_report(): report bootstrap results; jk(): jackknife estimation; jk_report(): report jackknife results; subset(): obtain subsets, one at a time; composition(): obtain compositions, one by one; ncompositions(): determine number of compositions; partition(): obtain partitions, one at a time; npartitionss(): determine number of partitions; rsubset(): draw random subset; rcomposition(): draw random composition; colvar(): variance, by column; meancolvar(): mean and variance, by column; variance0(): population variance; meanvariance0(): mean and population variance; mse(): mean squared error; colmse(): mean squared error, by column; sse(): sum of squared errors; colsse(): sum of squared errors, by column; benford(): Benford distribution; cauchy(): cumulative Cauchy-Lorentz dist.; cauchyden(): Cauchy-Lorentz density; cauchytail(): reverse cumulative Cauchy-Lorentz; invcauchy(): inverse cumulative Cauchy-Lorentz; rbinomial(): generate binomial random numbers; cebinomial(): cond. expect. of binomial r.v.; root(): Brent's univariate zero finder; nrroot(): Newton-Raphson zero finder; finvert(): univariate function inverter; integrate_sr(): univariate function integration (Simpson's rule); integrate_38(): univariate function integration (Simpson's 3/8 rule); ipolate(): linear interpolation; polint(): polynomial inter-/extrapolation; plot(): Draw twoway plot; _plot(): Draw twoway plot; panels(): identify nested panel structure; _panels(): identify panel sizes; npanels(): identify number of panels; nunique(): count number of distinct values; nuniqrows(): count number of unique rows; isconstant(): whether matrix is constant; nobs(): number of observations; colrunsum(): running sum of each column; linbin(): linear binning; fastlinbin(): fast linear binning; exactbin(): exact binning; makegrid(): equally spaced grid points; cut(): categorize data vector; posof(): find element in vector; which(): positions of nonzero elements; locate(): search an ordered vector; hunt(): consecutive search; cond(): matrix conditional operator; expand(): duplicate single rows/columns; _expand(): duplicate rows/columns in place; repeat(): duplicate contents as a whole; _repeat(): duplicate contents in place; unorder2(): stable version of unorder(); jumble2(): stable version of jumble(); _jumble2(): stable version of _jumble(); pieces(): break string into pieces; npieces(): count number of pieces; _npieces(): count number of pieces; invtokens(): reverse of tokens(); realofstr(): convert string into real; strexpand(): expand string argument; matlist(): display a (real) matrix; insheet(): read spreadsheet file; infile(): read free-format file; outsheet(): write spreadsheet file; callf(): pass optional args to function; callf_setup(): setup for mm_callf().

Modeling of Self-similar Traffic

Modeling of self-similar traffic is performed for the queuing system of G/M/1/K type using Weibull distribution. To study the self-similar traffic the simulation model is developed by using SIMULINK software package in MATLAB environment. Approximation of self-similar traffic on the basis of spline functions. Modeling self-similar traffic is carried outfor QS of W/M/1/K type using the Weibull distribution. Initial data are: the value of Hurst parameter H=0,65, the shape parameter of the distribution curve α≈0,7 and distribution parameter β≈0,0099. Considering that the self-similar traffic is characterized by the presence of "splashes" and long-termdependence between the moments of requests arrival in this study under given initial data it is reasonable to use linear interpolation splines.

Paleomagnetic and stable isotope measurements and distribution of benthic foraminifera in sediment core PS1388-3 from the Antarctic continental margin in the eastern Weddell Sea

A stable isotope record from the eastern Weddell Sea from 69°S is presented. For the first time, a 250,000-yr record from the Southern Ocean can be correlated in detail to the global isotope stratigraphy. Together with magnetostratigraphic, sedimentological and micropalaeontological data, the stratigraphic control of this record can be extended back to 910,000 yrs B.P. A time scale is constructed by linear interpolation between confirmed stratigraphic data points. The benthic d18O record (Epistominella exigua) reflects global continental ice volume changes during the Brunhes and late Matuyama chrons, whereas the planktonic isotopic record (Neogloboquadrina pachyderma) may be influenced by a meltwater lid caused by the nearby Antarctic ice shelf and icebergs. The worldwide climatic improvement during deglaciations is documented in the eastern Weddell Sea by an increase in production of siliceous plankton followed, with a time lag of approximately 10,000 yrs, by planktonic foraminifera production. Peak values in the difference between planktonic and benthic d13C records, which are 0.5 per mil higher during warm climatic periods than during times with expanded continental ice sheets, also suggest increased surface productivity during interglacials in the Southern Ocean.

Pressure and processed water levels from the Time Series Station Spiekeroog, 2005-2011

The quality of water level time series data strongly varies with periods of high and low quality sensor data. In this paper we are presenting the processing steps which were used to generate high quality water level data from water pressure measured at the Time Series Station (TSS) Spiekeroog. The TSS is positioned in a tidal inlet between the islands of Spiekeroog and Langeoog in the East Frisian Wadden Sea (southern North Sea). The processing steps will cover sensor drift, outlier identification, interpolation of data gaps and quality control. A central step is the removal of outliers. For this process an absolute threshold of 0.25m/10min was selected which still keeps the water level increase and decrease during extreme events as shown during the quality control process. A second important feature of data processing is the interpolation of gappy data which is accomplished with a high certainty of generating trustworthy data. Applying these methods a 10 years dataset (December 2002-December 2012) of water level information at the TSS was processed resulting in a seven year time series (2005-2011).

Spatial distribution of key zooplankton species using continuous plankton recorder (CPR) data from the North Atlantic (2000-2009)

The continuous plankton recorder (CPR) survey is an upper layer plankton monitoring program that has regularly collected samples, at monthly intervals, in the North Atlantic and adjacent seas since 1946. Water from approximately 6 m depth enters the CPR through a small aperture at the front of the sampler and travels down a tunnel where it passes through a silk filtering mesh of 270 µm before exiting at the back of the CPR. The plankton filtered on the silk is analyzed in sections corresponding to 10 nautical miles (approx. 3 m**3 of seawater filtered) and the plankton microscopically identified (Richardson et al., 2006 and reference therein). In the present study we used the CPR data to investigate the current basin scale distribution of C. finmarchicus (C5-C6), C. helgolandicus (C5-C6), C. hyperboreus (C5-C6), Pseudocalanus spp. (C6), Oithona spp. (C1-C6), total Euphausiida, total Thecosomata and the presence/absence of Cnidaria and the Phytoplankton Colour Index (PCI). The PCI, which is a visual assessment of the greenness of the silk, is used as an indicator of the distribution of total phytoplankton biomass across the Atlantic basin (Batten et al., 2003). Monthly data collected between 2000 and 2009 were gridded using the inverse-distance interpolation method, in which the interpolated values were the nodes of a 2 degree by 2 degree grid. The resulting twelve monthly matrices were then averaged within the year and in the case of the zooplankton the data were log-transformed (i.e. log10 (x+1).

Fine-silt luminescence dating and mineral composition of sediments from the Arctic Ocean

New geochronometers are needed for sediments of the Arctic Ocean spanning at least the last half million years, largely because oxygen-isotope stratigraphy is relatively ineffective in this ocean, and because other dating techniques require significant assumptions about sedimentation rates. Multi-aliquot luminescence sediment-dating procedures were applied to polymineral, fine-silt samples from 9 core-top and 37 deeper samples from 20 cores representing 19 sites across the Arctic Ocean. Most samples have independent age assignments and other known properties (e.g., % coarse fraction, % carbonate, U-Th isotopes). Thick-source alpha-particle counting indicates that for most regions the contribution of measured unsupported 230Th and 231Pa to calculated dose rates is

Calcareous nannofossils in Pliocene and Quaternary sediments of ODP Leg 117 holes

A total of 21 calcareous nannofossil datums was found in the upper Pliocene and Quaternary sediments recovered from the ocean floor of the North Atlantic during DSDP Leg 94. These datums were correlated to magnetostratigraphy, and ages were estimated by interpolation between magnetic reversals. Calcareous nannofossil assemblages from 549 samples recovered during ODP Leg 117 were studied in order to estimate the age of the sediments of Sites 720, 721, 722, and 731 drilled at the Indus Fan and the Owen Ridge in the Arabian Sea, Indian Ocean. We also showed that the datums above mentioned can be traced into the Indian Ocean. Two new species, namely Helicosphaera omanica and Reticulofenestra ampla, are described.

Le Messianisme chez Juifs : (150 av. J.-C. à 200 ap. J.-C.)

Mode of access: Internet.

Stability and convergence of general multistep and multivalue methods with variable step size.

Thesis--University of Illinois.

Automatic curve fitting for interactive display /

"AEC report no. C00-2383-002."