Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities. The purpose of NINJA is to study the sensitivity of existing gravitational-wave search algorithms using numerically generated waveforms and to foster closer collaboration between the numerical relativity and data analysis communities. We describe the results of the first NINJA analysis which focused on gravitational waveforms from binary black hole coalescence. Ten numerical relativity groups contributed numerical data which were used to generate a set of gravitational-wave signals. These signals were injected into a simulated data set, designed to mimic the response of the Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this data using search and parameter-estimation pipelines. Matched filter algorithms, un-modelled-burst searches and Bayesian parameter-estimation and model-selection algorithms were applied to the data. We report the efficiency of these search methods in detecting the numerical waveforms and measuring their parameters. We describe preliminary comparisons between the different search methods and suggest improvements for future NINJA analyses.Comment: 56 pages, 25 figures; various clarifications; accepted to CQ

Comparison of guideline- and model-based WWTP design for uncertain influent conditions

In this study, two methods for wastewater treatment plant (WWTP) dimensioning were compared: (1) a traditional guideline-based approach, and (2) a mechanistic model-based approach. The design outputs depended on uncertainties in correlated influent concentrations, which emphasises the importance of uncertainty analysis. The results showed that model-based design could simplify and reduce the time required for uncertainty and sensitivity analysis compared to a conventional design approach, in which the equations are solved manually and iteratively. A benefit of the conventional design approach was the simple interpretation of which factors limited the design capacity. In the end, this study shows the potential, as well as the need for, model-based design of WWTPs

Resilient dimensioning of wastewater treatment plants : Uncertainty analysis and simulation with applications to the activated sludge process

I Sverige saknas det formella riktlinjer för hur avloppsreningsverk ska dimensioneras. Det är inte ovanligt att verken dimensioneras utifrån erfarenhet och tumregler utan att det preciseras vilka osäkerheter som har hanterats. Projektet visar att flera svagheter med traditionell dimensionering skulle kunna vägas upp genom ökad användning av osäkerhetsanalys och processimulering.Wastewater treatment plants are commonly dimensioned based on rules of thumb and expertknowledge without a clear specification of how uncertainties have been handled. The impact of thedifferent assumptions can be quantified with uncertainty and sensitivity analysis. Weaknesses with traditional design methodology can potentially be mitigated by an increased use of simulation

Resilient dimensioning of wastewater treatment plants : Uncertainty analysis and simulation with applications to the activated sludge process

I Sverige saknas det formella riktlinjer för hur avloppsreningsverk ska dimensioneras. Det är inte ovanligt att verken dimensioneras utifrån erfarenhet och tumregler utan att det preciseras vilka osäkerheter som har hanterats. Projektet visar att flera svagheter med traditionell dimensionering skulle kunna vägas upp genom ökad användning av osäkerhetsanalys och processimulering.Wastewater treatment plants are commonly dimensioned based on rules of thumb and expertknowledge without a clear specification of how uncertainties have been handled. The impact of thedifferent assumptions can be quantified with uncertainty and sensitivity analysis. Weaknesses with traditional design methodology can potentially be mitigated by an increased use of simulation

To calibrate or not to calibrate, that is the question

Sensors used for control have become widespread in water resources recovery facilities during the strive for resource efficient operations. However, their accuracy is reliant on uncertain laboratory measurements, which are used for calibration and, in turn, to correct for sensor drift. At the same time, current sensor calibration practices are lacking clear theoretical understanding of how measurement uncertainties impact the final control action. The effects of a customarily, and ad hoc, applied calibration threshold are unknown, leading to the current situation where many wastewater treatment processes are controlled by measurements with unknown accuracy. To study how sensor accuracy is affected by calibration, including varying calibration thresholds, we developed a simple theoretical model with closed-form expressions based on the variance and bias in sensor and laboratory measurements. The model was then simulated to yield the results, which showed no practical gain of using a calibration threshold, apart from the situation when calibration is more time-consuming than validation. By contrast, the best accuracy was obtained when consistently executing calibration, which opposes common practice. Further, the sensor calibration error was shown to be transferred to the process, causing a similar deviation from the setpoint when the same sensor was used for control. This emphasizes the importance of minimizing laboratory measurement uncertainties during calibration, which otherwise directly impact operations. Due to these findings we strongly advice shifting mindset from considering calibration as a sequential detection and correction approach, towards an estimation approach, aiming to estimate bias magnitude and drift speed

Möjligheter med digitalisering och digitala tvillingar. Demonstrationsstudie på industriella och kommunala avloppsreningsverk.

En digital tvilling i form av en dynamisk processmodell kan användas för flera syften under hela livscykeln av ett kommunalt eller industriellt reningsverk. Syftet med detta projekt var att (1) demonstrera möjligheter för och (2) identifiera behov och genomförbarhet med en digital tvilling hos de anläggningsägare som ingår i projektet.För att demonstrera möjligheter användes LEVA i Lysekils ombyggnadsprojekt för Långeviks reningsverk som fallstudie. Med dataunderlag från förstudien implementerades en processmodell av det framtida reningsverket i en kommersiellt tillgänglig mjukvara. Denna baseras på att den befintliga för- och efterbehandlingen behålls medan det biologiska reningssteget byggs om till en MBBR-process. Som indata till modellen (temperatur, flöde och koncentrationer på inkommande och försedimenterat vatten) beaktades de förutsättningar som angivits i det förfrågningsunderlag som LEVA tagit fram. För att verifiera modellimplementeringen jämfördes modellresultaten med erfarenhetsbaserad kunskap om MBBR-processen. Resultaten visade att modellen i stort ger förväntade resultat vilket är viktigt för att verktyget skall få förtroende vid verklig tillämpning.Med den typ av digital tvilling som använts i projektet finns möjlighet att beskriva/modellera det inkommande avloppsvattnet med en högre detaljeringsgrad än vad som traditionellt görs vid ombyggnadsprojekt. För att demonstrera detta planerades och genomfördes en provtagningskampanj. Resultaten från denna var tyvärr inte tillförlitliga och därför användes i projektet standardvärden för inkommande vatten i projektet. Detta ökar osäkerheten i resultaten jämfört med om provtagningsresultaten hade funnits men förutsättningarna är fortfarande i enlighet med förfrågningsunderlaget.   I projektet har det sedan visats att det är möjligt att kombinera den digitala tvillingen med LCA-data för att beräkna klimatpåverkan för olika processutföranden, styrstrategier, val av energikälla och insatsvaror. Detta presenteras som ett stöd för jämförelse av olika anbud vid upphandling även om det kräver mera förarbete av både beställare och entreprenörer. Ett exempel är att byta styrstrategi för dosering av kolkälla kan spara upp till 19 ton CO2-ekvivalenter på ett år. Den digitala tvillingen kan också användas av LEVA under hela den nya processlösningens livstid från design och upphandling till införande och justeringar av driftstrategier och slutligen som ett stöd vid kontinuerlig drift.Som påbyggnad till konventionell processmodellering demonstrerades slutligen möjligheten att köra simulering i realtid och med indata från en verklig process. Implementeringen gjordes användarvänlig genom användning av mjukvaran Mediator som enkelt möjliggjorde sammankopplingen av signaler till/från ett styrsystem med kontaktpunkter definierade i simuleringsmjukvaran SIMBA#. Flera veckors stabil drift av systemet kunde visas. Tillämpningen anses dock för rudimentär för att kunna besvara frågor om krav på tidsupplösning, beräkningsprestanda och numerisk stabilitet. Under projektet genomfördes en behovs- och genomförbarhetsanalys genom informations- och kunskapsspridning vid ett flertal arbetsmöten och en avslutande workshop till vilken klustrets anläggningsägare bjöds in

LCA analysis of different WWTP processes

Wastewater treatment plants have the main objective to treat the incoming wastewater to meet specified discharge criteria. Different process configurations requiring different amount of resources such as energy and chemicals. The selection of process configuration can also impact the amount of energy produced from digestion of the sludge to biogas. In this study we compare the environmental impact of treating wastewater to two different levels of effluent quality (total phosphorus concentration, 1 mg P/L and 0.3 mg P/L) in three different process configurations using dynamic process modelling and life cycle assessment (LCA). The different processes studied were Pre-precipitation, Simultaneous precipitation and Biological phosphorous removal. Automatic process control in the models was used to achieve similar treatment results for the different processes. Operational data in the form of direct emissions to water and air, energy consumption, chemical consumption, production of sludge and biogas were generated by dynamic process simulations. The operational data were used in the LCA to calculate the environmental impact in five different categories, where global warming potential (GWP) also known as carbon footprint, was one. The results show that pre-precipitation gives the lowest GWP per m3 of treated water for both effluent standards. Bio-P gives the highest GWP.Den här rapporten finns endast på engelska. Svensk sammanfattning finns i rapporten

Yeast Volatomes Differentially Affect Larval Feeding in an Insect Herbivore

Yeasts form mutualistic interactions with insects. Hallmarks of this interaction include provision of essential nutrients, while insects facilitate yeast dispersal and growth on plant substrates. A phylogenetically ancient chemical dialogue coordinates this interaction, where the vocabulary, the volatile chemicals that mediate the insect response, remains largely unknown. Here, we used gas chromatography-mass spectrometry, followed by hierarchical cluster and orthogonal partial least-squares discriminant analyses, to profile the volatomes of six Metschnikowia spp., Cryptococcus nemorosus, and brewer's yeast (Saccharomyces cerevisiae). The yeasts, which are all found in association with insects feeding on foliage or fruit, emit characteristic, species-specific volatile blends that reflect the phylogenetic context. Species specificity of these volatome profiles aligned with differential feeding of cotton leafworm (Spodoprera littoralis) larvae on these yeasts. Bioactivity correlates with yeast ecology; phylloplane species elicited a stronger response than fruit yeasts, and larval discrimination may provide a mechanism for establishment of insect-yeast associations. The yeast volatomes contained a suite of insect attractants known from plant and especially floral headspace, including (Z)-hexenyl acetate, ethyl (2E,4Z)-deca-2,4-dienoate (pear ester), (3E)-4,8-dimethylnona-1,3,7-triene (DMNT), linalool, alpha-terpineol, beta-myrcene, or (E,E)-alpha-farnesene. A wide overlap of yeast and plant volatiles, notably floral scents, further emphasizes the prominent role of yeasts in plant-microbe-insect relationships, including pollination. The knowledge of insect-yeast interactions can be readily brought to practical application, as live yeasts or yeast metabolites mediating insect attraction provide an ample tool-box for the development of sustainable insect management. IMPORTANCE Yeasts interface insect herbivores with their food plants. Communication depends on volatile metabolites, and decoding this chemical dialogue is key to understanding the ecology of insect-yeast interactions. This study explores the volatomes of eight yeast species which have been isolated from foliage, from flowers or fruit, and from plant-feeding insects. These yeasts each release a rich bouquet of volatile metabolites, including a suite of known insect attractants from plant and floral scent. This overlap underlines the phylogenetic dimension of insect-yeast associations, which according to the fossil record long predate the appearance of flowering plants. Volatome composition is characteristic for each species, aligns with yeast taxonomy, and is further reflected by a differential behavioral response of cotton leafworm larvae, which naturally feed on foliage of a wide spectrum of broad-leaved plants. Larval discrimination may establish and maintain associations with yeasts and is also a substrate for designing sustainable insect management techniques

Balancing effluent quality, economic cost and greenhouse gas emissions during the evaluation of (plant-wide) control/operational strategies in WWTPs

The objective of this paper was to show the potential additional insight that result from adding greenhouse gas (GHG) emissions to plant performance evaluation criteria, such as effluent quality (EQI) and operational cost (OCI) indices, when evaluating (plant-wide) control/operational strategies in wastewater treatment plants (WWTPs). The proposed GHG evaluation is based on a set of comprehensive dynamic models that estimate the most significant potential on-site and off-site sources of CO2, CH4 and N2O. The study calculates and discusses the changes in EQI, OCI and the emission of GHGs as a consequence of varying the following four process variables: (i) the set point of aeration control in the activated sludge section; (ii) the removal efficiency of total suspended solids (TSS) in the primary clarifier; (iii) the temperature in the anaerobic digester; and (iv) the control of the flow of anaerobic digester supernatants coming from sludge treatment. Based upon the assumptions built into the model structures, simulation results highlight the potential undesirable effects of increased GHG production when carrying out local energy optimization of the aeration system in the activated sludge section and energy recovery from the AD. Although off-site CO2 emissions may decrease, the effect is counterbalanced by increased N2O emissions, especially since N2O has a 300-fold stronger greenhouse effect than CO2. The reported results emphasize the importance and usefulness of using multiple evaluation criteria to compare and evaluate (plant-wide) control strategies in a WWTP for more informed operational decision makin