Computational methods for tactical simulations

Tämä taktiikan tutkimus keskittyy tietokoneavusteisen simuloinnin laskennallisiin menetelmiin, joita voidaan käyttää taktisen tason sotapeleissä. Työn tärkeimmät tuotokset ovat laskennalliset mallit todennäköisyyspohjaisen analyysin mahdollistaviin taktisen tason taistelusimulaattoreihin, joita voidaan käyttää vertailevaan analyysiin joukkue-prikaatitason tarkastelutilanteissa. Laskentamallit keskittyvät vaikuttamiseen. Mallit liittyvät vahingoittavan osuman todennäköisyyteen, jonka perusteella vaikutus joukossa on mallinnettu tilakoneina ja Markovin ketjuina. Edelleen näiden tulokset siirretään tapahtumapuuanalyysiin operaation onnistumisen todennäköisyyden osalta. Pienimmän laskentayksikön mallinnustaso on joukkue- tai ryhmätasolla, jotta laskenta-aika prikaatitason sotapelitarkasteluissa pysyisi riittävän lyhyenä samalla, kun tulokset ovat riittävän tarkkoja suomalaiseen maastoon. Joukkueiden mies- ja asejärjestelmävahvuudet ovat jakaumamuodossa, eivätkä yksittäisiä lukuja. Simuloinnin integroinnissa voidaan käyttää asejärjestelmäkohtaisia predictor corrector –parametreja, mikä mahdollistaa aika-askelta lyhytaikaisempien taistelukentän ilmiöiden mallintamisen. Asemallien pohjana ovat aiemmat tutkimukset ja kenttäkokeet, joista osa kuuluu tähän väitöstutkimukseen. Laskentamallien ohjelmoitavuus ja käytettävyys osana simulointityökalua on osoitettu tekijän johtaman tutkijaryhmän ohjelmoiman ”Sandis”- taistelusimulointiohjelmiston avulla, jota on kehitetty ja käytetty Puolustusvoimien Teknillisessä Tutkimuslaitoksessa. Sandikseen on ohjelmoitu karttakäyttöliittymä ja taistelun kulkua simuloivia laskennallisia malleja. Käyttäjä tai käyttäjäryhmä tekee taktiset päätökset ja syöttää nämä karttakäyttöliittymän avulla simulointiin, jonka tuloksena saadaan kunkin joukkuetason peliyksikön tappioiden jakauma, keskimääräisten tappioiden osalta kunkin asejärjestelmän aiheuttamat tappiot kuhunkin maaliin, ammuskulutus ja radioyhteydet ja niiden tila sekä haavoittuneiden evakuointi-tilanne joukkuetasolta evakuointisairaalaan asti. Tutkimuksen keskeisiä tuloksia (kontribuutio) ovat 1) uusi prikaatitason sotapelitilanteiden laskentamalli, jonka pienin yksikkö on joukkue tai ryhmä; 2) joukon murtumispisteen määritys tappioiden ja haavoittuneiden evakuointiin sitoutuvien taistelijoiden avulla; 3) todennäköisyyspohjaisen riskianalyysin käyttömahdollisuus vertailevassa tutkimuksessa sekä 4) kokeellisesti testatut tulen vaikutusmallit ja 5) toimivat integrointiratkaisut. Työ rajataan maavoimien taistelun joukkuetason todennäköisyysjakaumat luovaan laskentamalliin, kenttälääkinnän malliin ja epäsuoran tulen malliin integrointimenetelmineen sekä niiden antamien tulosten sovellettavuuteen. Ilmasta ja mereltä maahan -asevaikutusta voidaan tarkastella, mutta ei ilma- ja meritaistelua. Menetelmiä soveltavan Sandis -ohjelmiston malleja, käyttötapaa ja ohjelmistotekniikkaa kehitetään edelleen. Merkittäviä jatkotutkimuskohteita mallinnukseen osalta ovat muun muassa kaupunkitaistelu, vaunujen kaksintaistelu ja maaston vaikutus tykistön tuleen sekä materiaalikulutuksen arviointi.

Qualitative Characteristics and Quantitative Measures of Solution's Reliability in Discrete Optimization: Traditional Analytical Approaches, Innovative Computational Methods and Applicability

The purpose of this thesis is twofold. The first and major part is devoted to sensitivity analysis of various discrete optimization problems while the second part addresses methods applied for calculating measures of solution stability and solving multicriteria discrete optimization problems. Despite numerous approaches to stability analysis of discrete optimization problems two major directions can be single out: quantitative and qualitative. Qualitative sensitivity analysis is conducted for multicriteria discrete optimization problems with minisum, minimax and minimin partial criteria. The main results obtained here are necessary and sufficient conditions for different stability types of optimal solutions (or a set of optimal solutions) of the considered problems. Within the framework of quantitative direction various measures of solution stability are investigated. A formula for a quantitative characteristic called stability radius is obtained for the generalized equilibrium situation invariant to changes of game parameters in the case of the H¨older metric. Quality of the problem solution can also be described in terms of robustness analysis. In this work the concepts of accuracy and robustness tolerances are presented for a strategic game with a finite number of players where initial coefficients (costs) of linear payoff functions are subject to perturbations. Investigation of stability radius also aims to devise methods for its calculation. A new metaheuristic approach is derived for calculation of stability radius of an optimal solution to the shortest path problem. The main advantage of the developed method is that it can be potentially applicable for calculating stability radii of NP-hard problems. The last chapter of the thesis focuses on deriving innovative methods based on interactive optimization approach for solving multicriteria combinatorial optimization problems. The key idea of the proposed approach is to utilize a parameterized achievement scalarizing function for solution calculation and to direct interactive procedure by changing weighting coefficients of this function. In order to illustrate the introduced ideas a decision making process is simulated for three objective median location problem. The concepts, models, and ideas collected and analyzed in this thesis create a good and relevant grounds for developing more complicated and integrated models of postoptimal analysis and solving the most computationally challenging problems related to it.

Computational visual quality of digitally printed images

The problem of understanding how humans perceive the quality of a reproduced image is of interest to researchers of many fields related to vision science and engineering: optics and material physics, image processing (compression and transfer), printing and media technology, and psychology. A measure for visual quality cannot be defined without ambiguity because it is ultimately the subjective opinion of an “end-user” observing the product. The purpose of this thesis is to devise computational methods to estimate the overall visual quality of prints, i.e. a numerical value that combines all the relevant attributes of the perceived image quality. The problem is limited to consider the perceived quality of printed photographs from the viewpoint of a consumer, and moreover, the study focuses only on digital printing methods, such as inkjet and electrophotography. The main contributions of this thesis are two novel methods to estimate the overall visual quality of prints. In the first method, the quality is computed as a visible difference between the reproduced image and the original digital (reference) image, which is assumed to have an ideal quality. The second method utilises instrumental print quality measures, such as colour densities, measured from printed technical test fields, and connects the instrumental measures to the overall quality via subjective attributes, i.e. attributes that directly contribute to the perceived quality, using a Bayesian network. Both approaches were evaluated and verified with real data, and shown to predict well the subjective evaluation results.

Embedding, Extraction and Detection of Digital Watermark in Spectral Images

Tässä diplomityössä tutkitaan tekniikoita, joillavesileima lisätään spektrikuvaan, ja menetelmiä, joilla vesileimat tunnistetaanja havaitaan spektrikuvista. PCA (Principal Component Analysis) -algoritmia käyttäen alkuperäisten kuvien spektriulottuvuutta vähennettiin. Vesileiman lisääminen spektrikuvaan suoritettiin muunnosavaruudessa. Ehdotetun mallin mukaisesti muunnosavaruuden komponentti korvattiin vesileiman ja toisen muunnosavaruuden komponentin lineaarikombinaatiolla. Lisäyksessä käytettävää parametrijoukkoa tutkittiin. Vesileimattujen kuvien laatu mitattiin ja analysoitiin. Suositukset vesileiman lisäykseen esitettiin. Useita menetelmiä käytettiin vesileimojen tunnistamiseen ja tunnistamisen tulokset analysoitiin. Vesileimojen kyky sietää erilaisia hyökkäyksiä tarkistettiin. Diplomityössä suoritettiin joukko havaitsemis-kokeita ottamalla huomioon vesileiman lisäyksessä käytetyt parametrit. ICA (Independent Component Analysis) -menetelmää pidetään yhtenä mahdollisena vaihtoehtona vesileiman havaitsemisessa.

Oxygen adsorption on Cu(510)

Tässä työssä on tutkittu kuparin (510)-askelpinnan reaktiivisuutta käyttäen apuna kvanttimekaanisia ab initio laskentamenetelmiä. Tutkimus on toteutettu laskemalla happiatomin adsorptioenergia ja tilatiheys erilaisissa potentiaalisissa adsorptiopaikoissa pinnalla. Myös happimolekyylin adsorptiota ja hajoamista ontarkasteltu laskemalla pintaa lähestyvälle molekyylille potentiaalienergiapintoja. Energiapintojen tuloksia on myös täydennetty kvanttimekaanisilla molekyylidynamiikkalaskuilla. Metallisia askelpintoja pidetään yleisesti sileitä pintoja reaktiivisempina happea kohtaan, johtuen askeleen reunan pienentävästä vaikutuksesta molekyylin hajoamisen tiellä olevaan energiavaliin. On kuitenkin olemassa myös tuloksia, jotka osoittavat hapen tarttumisprosessin olevan hallitseva juuri terassialueella, askeleen reunan sijasta. Tässä työssä on todettu hapen adsorboituvan Cu(510)-pinnalla tehokkaimmin juuri terassilla olevaan hollow-paikkaan. Myös adsorptioenergiat ovat tällä pinnalla pienempiä kuin sileällä (100)-pinnalla. Potentiaalienergiapintojen perusteella Cu(510)-pinnan todetaan myös olevan vähemmän reaktiivinen kuin askelpintojen yleisesti odotetaan olevan, vaikka askeleen reunan todetaankin pienentävän happiatominhajoamisen esteenä olevaa energiavallia.

Quantitative proteomics in the characterization of T helper lymphocyte differentiation

The term proteome is used to define the complete set of proteins expressed in cells or tissues of an organism at a certain timepoint. Respectively, proteomics is used to describe the methods, which are used to study such proteomes. These methods include chromatographic and electrophoretic techniques for protein or peptide fractionation, mass spectrometry for their identification, and use of computational methods to assist the complicated data analysis. A primary aim in this Ph.D. thesis was to set-up, optimize, and develop proteomics methods for analysing proteins extracted from T-helper (Th) lymphocytes. First, high-throughput LC-MS/MS and ICAT labeling methods were set-up and optimized for analysing the microsomal fraction proteins extracted from Th lymphocytes. Later, iTRAQ method was optimized to study cytokine regulated protein expression in the nuclei of Th lymphocytes. High-throughput LC-MS/MS analyses, like ICAT and iTRAQ, produce large quantities of data and robust software and data analysis pipelines are needed. Therefore, different software programs used for analysing such data were evaluated. Moreover, a pre-filtering algorithm was developed to classify good-quality and bad-quality spectra prior to the database searches. Th-lymphocytes can differentiate into Th1 or Th2 cells based on surrounding antigens, co-stimulatory molecules, and cytokines. Both subsets have individual cytokine secretion profiles and specific functions. Th1 cells participate in the cellular immunity against intracellular pathogens, while Th2 cells have important role in the humoral immunity against extracellular parasites. An abnormal response of Th1 and Th2 cells and imbalance between the subsets are charasteristic of several diseases. Th1 specific reactions and cytokines have been detected in autoimmune diseases, while Th2 specific response and cytokine profile is common in allergy and asthma. In this Ph. D. thesis mass spectrometry-based proteomics was used to study the effects of Th1 and Th2 promoting cytokines IL-12 and IL-4 on the proteome of Th lymphocytes. Characterization of microsomal fraction proteome extracted from IL-12 treated lymphobasts and IL-4 stimulated cord blood CD4+ cells resulted in finding of cytokine regulated proteins. Galectin-1 and CD7 were down-regulated in IL-12 treated cells, while IL-4 stimulation decreased the expression of STAT1, MXA, GIMAP1, and GIMAP4. Interestingly, the transcription of both GIMAP genes was up-regulated in Th1 polarized cells and down-regulated in Th2 promoting conditions.

First principles modeling of metallic alloys and alloy surfaces

By alloying metals with other materials, one can modify the metal’s characteristics or compose an alloy which has certain desired characteristics that no pure metal has. The field is vast and complex, and phenomena that govern the behaviour of alloys are numerous. Theories cannot penetrate such complexity, and the scope of experiments is also limited. This is why the relatively new field of ab initio computational methods has much to give to this field. With these methods, one can extend the understanding given by theories, predict how some systems might behave, and be able to obtain information that is not there to see in physical experiments. This thesis pursues to contribute to the collective knowledge of this field in the light of two cases. The first part examines the oxidation of Ag/Cu, namely, the adsorption dynamics and oxygen induced segregation of the surface. Our results demonstrate that the presence of Ag on the Cu(100) surface layer strongly inhibits dissociative adsorption. Our results also confirmed that surface reconstruction does happen, as experiments predicted. Our studies indicate that 0.25 ML of oxygen is enough for Ag to diffuse towards the bulk, under the copper oxide layer. The other part elucidates the complex interplay of various energy and entropy contributions to the phase stability of paramagnetic duplex steel alloys. We were able to produce a phase stability map from first principles, and it agrees with experiments rather well. Our results also show that entropy contributions play a very important role on defining the phase stability. This is, to the author’s knowledge, the first ab initio study upon this subject.

Algorithmic Techniques in Gene Expression Processing. From Imputation to Visualization

The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

Investigation of the fatigue performance of welded duplex stainless steel

Diplomityössä tutkitaan hitsatun duplex-teräksen, laatu: EN 1.4462 (Outokumpu laatu 2205) väsymislujuutta. Tutkimusmetodologia noudattaa sekä kokeellisia että laskennallisia menetelmiä. Kokeelliset menetelmät sisältävät hitsatun teräksen väsytystestaukset laboratoriossa, hitsausten jälkikäsittelyt (HiFIT) sekä perusaineelle ja hitseille tehtävät metallurgiset tutkimukset. Väsytyskokeista saatavia tuloksia verrataan kansainvälisen hitsausinstituutin (IIW) vahvistamiin rakennekohtaisiin standardeihin sekä kirjallisuudessa esiintyviin tutkimustuloksiin. Laskennalliset menetelmät sisältävät vertailulaskelmia tehollisen lovijännityksen (ENS) menetelmää hyödyntäen. Tehollisen lovijännityksen menetelmässä liitoksissa vaikuttavat teholliset lovijännitykset selvitetään elementtimenetelmän (FEM) avulla. Tulokset vahvistavat, että hitsauksella ja hitsausten jälkikäsittelyllä on suuri merkitys rakenteen kestoikään. Suurin osa väsytyskokeiden tuloksista osoitti parempia väsymiskestävyyden arvoja kuin rakennekohtaiset standardit, mutta liitosten liitosvirheiden todettiin heikentävän väsytyskestävyyttä. Jälkikäsittelyiden todettiin parantavan liitosten väsymiskestävyyden tuloksia ja todettiin tulosten olevan hyödynnettävissä mitoituksessa.

GIS-based approach for optimization of onshore wind park infrastructure alignment in Finland

Wind power is a rapidly developing, low-emission form of energy production. In Fin-land, the official objective is to increase wind power capacity from the current 1 005 MW up to 3 500–4 000 MW by 2025. By the end of April 2015, the total capacity of all wind power project being planned in Finland had surpassed 11 000 MW. As the amount of projects in Finland is record high, an increasing amount of infrastructure is also being planned and constructed. Traditionally, these planning operations are conducted using manual and labor-intensive work methods that are prone to subjectivity. This study introduces a GIS-based methodology for determining optimal paths to sup-port the planning of onshore wind park infrastructure alignment in Nordanå-Lövböle wind park located on the island of Kemiönsaari in Southwest Finland. The presented methodology utilizes a least-cost path (LCP) algorithm for searching of optimal paths within a high resolution real-world terrain dataset derived from airborne lidar scannings. In addition, planning data is used to provide a realistic planning framework for the anal-ysis. In order to produce realistic results, the physiographic and planning datasets are standardized and weighted according to qualitative suitability assessments by utilizing methods and practices offered by multi-criteria evaluation (MCE). The results are pre-sented as scenarios to correspond various different planning objectives. Finally, the methodology is documented by using tools of Business Process Management (BPM). The results show that the presented methodology can be effectively used to search and identify extensive, 20 to 35 kilometers long networks of paths that correspond to certain optimization objectives in the study area. The utilization of high-resolution terrain data produces a more objective and more detailed path alignment plan. This study demon-strates that the presented methodology can be practically applied to support a wind power infrastructure alignment planning process. The six-phase structure of the method-ology allows straightforward incorporation of different optimization objectives. The methodology responds well to combining quantitative and qualitative data. Additional-ly, the careful documentation presents an example of how the methodology can be eval-uated and developed as a business process. This thesis also shows that more emphasis on the research of algorithm-based, more objective methods for the planning of infrastruc-ture alignment is desirable, as technological development has only recently started to realize the potential of these computational methods.

Lossless Compression Methods for Multispectral Images: Development and Comparisons

Main purpose of this thesis is to introduce a new lossless compression algorithm for multispectral images. Proposed algorithm is based on reducing the band ordering problem to the problem of finding a minimum spanning tree in a weighted directed graph, where set of the graph vertices corresponds to multispectral image bands and the arcs’ weights have been computed using a newly invented adaptive linear prediction model. The adaptive prediction model is an extended unification of 2–and 4–neighbour pixel context linear prediction schemes. The algorithm provides individual prediction of each image band using the optimal prediction scheme, defined by the adaptive prediction model and the optimal predicting band suggested by minimum spanning tree. Its efficiency has been compared with respect to the best lossless compression algorithms for multispectral images. Three recently invented algorithms have been considered. Numerical results produced by these algorithms allow concluding that adaptive prediction based algorithm is the best one for lossless compression of multispectral images. Real multispectral data captured from an airplane have been used for the testing.

Computational Evaluation of Print Unevenness According to Human Vision

Print quality and the printability of paper are very important attributes when modern printing applications are considered. In prints containing images, high print quality is a basic requirement. Tone unevenness and non uniform glossiness of printed products are the most disturbing factors influencing overall print quality. These defects are caused by non ideal interactions of paper, ink and printing devices in high speed printing processes. Since print quality is a perceptive characteristic, the measurement of unevenness according to human vision is a significant problem. In this thesis, the mottling phenomenon is studied. Mottling is a printing defect characterized by a spotty, non uniform appearance in solid printed areas. Print mottle is usually the result of uneven ink lay down or non uniform ink absorption across the paper surface, especially visible in mid tone imagery or areas of uniform color, such as solids and continuous tone screen builds. By using existing knowledge on visual perception and known methods to quantify print tone variation, a new method for print unevenness evaluation is introduced. The method is compared to previous results in the field and is supported by psychometric experiments. Pilot studies are made to estimate the effect of optical paper characteristics prior to printing, on the unevenness of the printed area after printing. Instrumental methods for print unevenness evaluation have been compared and the results of the comparison indicate that the proposed method produces better results in terms of visual evaluation correspondence. The method has been successfully implemented as ail industrial application and is proved to be a reliable substitute to visual expertise.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

Statistical segmentation methods and color variance analysis of retinal images

In this research, the effectiveness of Naive Bayes and Gaussian Mixture Models classifiers on segmenting exudates in retinal images is studied and the results are evaluated with metrics commonly used in medical imaging. Also, a color variation analysis of retinal images is carried out to find how effectively can retinal images be segmented using only the color information of the pixels.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.