Informational Entropy Approach for Rating Curve Assessment in Rough and Smooth Irrigation Ditch

The assessment of water discharge in open channel flow is one of the most crucial issues for hydraulic engineers in the fields of water resources management, river dynamics, eco-hydraulics, irrigation, hydraulic structure design, etc. Recent studies state that the entropy velocity law allows expeditive methodology for discharge estimation and rating curve development due to the simple mathematical formulation and implementation. A lot of works have been developed based on the entropy velocity profile supporting measurements in lab for rating curve assessment in regular ditch flows showing a good performance. The present work deals with the use of entropy velocity profile approach in order to give a general framework of threats and opportunities related to robust operational application of such laws in the field of rating curve assessment. The analysis has been carried on a laboratory flume with regular roughness under controlled boundary conditions and different stages generating an exhaustive dashboard for the better appraisal of the approaches. Finally, entropy model may represent a robust and useful tool for the water discharge assessment in rough ditches

Effect of bed roughness on 1-D entropy velocity distribution in open channel flow

A theoretic-analytical formulation, based on entropy velocity profile law and classical relationships for uniform flow and friction factor, is proposed enlightening the general logarithmic relationship existing between the parameter Φ(M), defined as mean cross section velocity over maximum velocity, and the ratio water depth/bed roughness (D/d). The relationship Φ(M)-D/d has been applied to a relevant set of experimental velocity measurement data collected both in laboratory and in field, showing different behaviour between small scale and large-intermediate roughness flows. In particular, the roughness influence becomes remarkable whenever shallow water flow conditions occur, that is when the ratio between the flow depth and the roughness height is less than 4, while Φ(M) tends to be constant as the value of D/d increases

Entropy parameter estimation in large-scale roughness open channel

The entropy model allows estimating, in an expeditive way, both water discharge and flow velocity field in open channels. In fact, such model presents an almost simple analytical structure, based on the evaluation of a single parameter calculated through the ratio between the mean and maximum flow velocities in the cross section. Recent studies have demonstrated that, for large-scale roughness, the evaluation of the entropy parameter seems to be affected by the local conditions near the bed. In order to investigate such influence, the present work proposes an explicit relationship between the entropy parameter and the relative submergence. This relation was validated using data collected in a rectangular tilting flume of laboratory, where the bed roughness was composed by elements of regular shape such as spheres. Several tests were performed in conditions of large-scale roughness (1.9<D/d<6.4) and for different values of slope (0.05%<i<1%) and water discharge (7l/s<Q<76l/s). The method shows a good agreement between the observed and calculated data for both the velocity profiles and water discharges

INFLUENCE OF BED ROUGHNESS AND CROSS SECTION GEOMETRY ON MEDIUM AND MAXIMUM VELOCITY RATIO IN OPEN CHANNEL FLOW

The paper deals with the analytic-theoretical derivation of the relationships between the entropic quantity Φ(M), representing the ratio between the mean and maximum flow velocity, and the relative submergence and aspect ratio, using classical open channel flow equations. Φ(M) is found to be highly dependent on the relative submergence when large or intermediate roughness scale occur, while it might be assumed almost constant for a small roughness scale. Furthermore, considering the hydraulic geometry relationships, it is attempted to relate the relative submergence to the aspect ratio of flow through a log-relationship whose coefficients depend on the local bed slope, with an important implication for hydrological practices. Then, a practical relation between Φ(M) and aspect ratio is proposed and validated in the operative chain for discharge assessment, showing high robustness and stability. The proposed model has been applied to a set of experimental velocity data collected in gaged river sites with different geometric and hydraulic characteristics as well as low, medium and high flows

VULNERABILITY ASSESSMENT FOR PRELIMINARY FLOOD RISK MAPPING AND MANAGEMENT IN COASTAL AREAS

Planning and management of coastal environment, both terrestrial and marine, is affected by several actions in environment resource conservation and improvement paying specific attention to risk forecasting and preventing. In such context the EU flood Directive 2007/60/EC, which requires Member States the assessment and management of flood risk, and the EU water framework Directive (2000/60/EC) are the key factors in the integrated river basin management to assure an efficient and rational use of resources. Afterwards, coastal risk assessment and mapping is a propaedeutic phase to plan and manage coastal areas. In this work risk analysis refers to the results obtained by the combined application of coastal flooding and erosion risks in the activities carried out to prepare Regional Coast Management Plan for the Ionian coast of Basilicata Region located in the south of Italy. In order to define the driving forces acting on the shore, high resolution lidar data, bathymetric information and wave climate statistics acquired by meteorological analyses on wind field data referred to different acquisition times are used. The systemic vulnerability estimation is achieved by composing both hazard factors combined in the Criticality Coastal Index depending on of the assessment of Coastal Flood Index and Coastal Erosion Index based on morphologic and socio-economic variables

Two-Phase Depth-Integrated Model for Unsteady River Flow

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Glass transition and cooperative rearranging regions in amorphous thermoplastic nanocomposites

The aim of this work was to study the effect of nanofillers on the structural relaxation phenomena occurring in amorphous poly(ethylene-terephthalate)/poly(cyclohexane-dimethanol terephthalate) copolymer (PET/PCHDMT) nanocomposites in correspondence with the glass transition temperature. PET/PCHDMT nanocomposites were prepared by melt mixing with an organicmodified montmorillonite at different processing temperatures. Differential scanning calorimetry analysis revealed that addition of the organic modifier alone causes a decrease of the glass transition temperature and an increase of the specific heat discontinuity. Nanocomposites showed a higher glass transition temperature and a lower specific heat discontinuity compared with samples obtained by adding organic modifier to PET/PCHDMT. Both effects were more relevant for samples processed at lower temperatures. Therefore, the glass transition temperature was studied by introducing the concept of fictive temperature and relaxation time. It was found that nanocomposites have a higher apparent activation energy and an increased size of cooperatively rearranging regions compared with neat PET/PCHDMT. Both effects are more relevant for nanocomposites processed at lower temperatures. All the discussed effects are explained by considering the enhanced confinement of PET/PCHDMT macromolecules, due to the presence of intercalated lamellae of organofiller. The efficiency of intercalation is increased by decreased processing temperature, which involves an increase of the nano-confinement area of the polymer

How to Select Knowledge Management Systems: A Framework to Support Managers

The purpose of this paper is to provide a methodological framework which could support managers in the selection of Knowledge Management Systems. The framework is based on the Analytic Hierarchy Process approach. Several aspects should draw the attention of an organization’s upper level of management seeking to implement a Knowledge Management System and many specific issues have to be considered. As such, the framework has been built by making use of an ad‐hoc hierarchical structure, where each singular specificity is described and compared, second‐order criteria are studied and analysed, and optional decisions are highlighted and evaluated. This methodological framework offers a good applicability to different business contexts, since its hierarchical arrangement suits most of the needs of numerous organizations. Consequently, it can be regarded as a holistic approach able to assist decision makers in their Knowledge Management System selection process

Analisi e validazione di tecniche di Reinforcement Learning su sensori low-power per applicazioni IoT di monitoraggio

Lo studio di questa tesi è stato condotto in un periodo storico caratterizzato da un'elevata presenza di dispositivi connessi alla rete che sono in grado di percepire, elaborare, produrre e scambiare un elevato numero di dati con altri dispositivi. Tali dispositivi, connessi tra loro e in continua comunicazione, costituiscono l'Internet of Things, una rete che trova applicazione in diversi campi risolvendo problemi, creando opportunità e proponendo nuove sfide. In questo studio la sfida raccolta è stata quella di affiancare l'intelligenza artificiale a dispositivi IoT in modo da renderli capaci di apprendere, in autonomia, come svolgere il proprio lavoro in modo efficiente e cercando di risparmiare energia. Lo studio è stato condotto mediante simulazione di un sistema di monitoraggio ambientale costituito da un dispositivo governato da agente decisionale di Q-learning che trasmette informazioni ad attuatori simulati, che intervengono sui parametri ambientali, e a un centro di raccolta dati simulato. Le prestazioni del dispositivo smart sono state confrontate con quelle di altri due dispositivi di controllo semplici. Uno dei due dispositivi di controllo, detto diligent, ha avuto il compito di rappresentare il dispositivo più reattivo in merito agli interventi sui valori dei parametri ambientali. L'altro dispositivo semplice, detto energy saver, ha avuto il compito di risolvere il problema riducendo il numero di operazioni di sense utilizzate per entrare a conoscenza dei valori dei parametri ambientali. Lo studio ha dimostrato come il Reinforcement Learning sia effettivamente in grado di risolvere problemi descrivibili tramite modellazione di catene di decisioni per compiti a circuito chiuso dotati di stati che godono della proprietà di Markov. I risultati mostrano come il dispositivo smart sia stato in grado di apprendere autonomamente come comportarsi per svolgere il compito assegnato combinando i punti di forza dei dispositivi di controllo